iii

CONTENTS

Abstract ..................................................................................................................................................................................1

Introduction ............................................................................................................................................................................2

Purpose and scope .........................................................................................................................................................4

Previous investigations ..................................................................................................................................................4

Acknowledgments .........................................................................................................................................................5

Description of the study area .........................................................................................................................................5

Climate..................................................................................................................................................................5

Hydrology, soils, and topography .........................................................................................................................5

Water use...............................................................................................................................................................6

Model development................................................................................................................................................................6

Overview of the hydrological simulation program - FORTRAN (HSPF).....................................................................6

Model assumptions ........................................................................................................................................................8

Watershed segmentation ................................................................................................................................................8

Land use.........................................................................................................................................................................8

Development of nutrient application rates...................................................................................................................11

Animal counts, animal units, and the manure land-use category........................................................................11

Organic fertilizer calculations.............................................................................................................................13

Nutrient requirements and goal yields ................................................................................................................13

Total nutrient applications...................................................................................................................................13

Method of fertilizer application ..........................................................................................................................18

Schedule of organic fertilizer application ...........................................................................................................18

Schedule of mineral fertilizer application...........................................................................................................18

Planting and harvesting dates..............................................................................................................................20

Atmospheric deposition...............................................................................................................................................20

On-site wastewater disposal system information ........................................................................................................20

Point sources................................................................................................................................................................20

Meteorological data .....................................................................................................................................................21

Development of water-quality data base for model calibration...................................................................................22

Model calibration approach..................................................................................................................................................22

Calibration of hydrology .............................................................................................................................................23

Parameter estimation...........................................................................................................................................23

Objective function for parameter estimation ......................................................................................................23

Calibration of total suspended solids and nutrients .....................................................................................................24

Analysis of model calibration and results ............................................................................................................................24

Calibration of hydrology .............................................................................................................................................26

Annual and monthly water balance.....................................................................................................................26

Mean daily streamflow time series .....................................................................................................................28

Calibration of total suspended solids...........................................................................................................................31

Annual edge-of-stream yields .............................................................................................................................31

Hourly concentration time series ........................................................................................................................31

Calibration of nutrients................................................................................................................................................31

Annual edge-of-stream yields .............................................................................................................................34

Hourly concentration time series ........................................................................................................................36

Summary and conclusions....................................................................................................................................................40

References cited ...................................................................................................................................................................40
iv

Figures

1a. Hydrogeomorphic regions of the Delmarva Peninsula and location of the Delaware Inland Bays

watershed ...........................................................................................................................................................2

1b. Detailed view of the Delaware Inland Bays watershed, Sussex County, Delaware................................................3

2. Soils map for the Inland Bays watershed showing percent organic matter, soil permeability, and a

hydrologic characteristics grouping code (STATSGO group number)...............................................................7

3. Hydrological Simulation Program–FORTRAN (HSPF) Inland Bays watershed model

segmentation, locations of U.S. Geological Survey stream-gaging stations, hourly and

daily precipitation stations, and the major nutrient point source near Georgetown, Delaware...........................9

4. Generalized land-use map of the Delaware Inland Bays watershed .....................................................................12

5. Crop hectare allocations for the model..................................................................................................................13

6. Grouping of model segments with identical parameter values, indicating the calibration model

segment source for those values ........................................................................................................................25

7. Monthly simulated and observed streamflow for the six calibrated basins during 1999 ......................................27

8. Simulated and observed daily flows, with daily precipitation intensity, for the six calibrated

basins during 1999.............................................................................................................................................29

9. Simulated daily edge-of-stream streamflow components and total streamflow simulated at

the end of the reach for the five single-segment calibrated basins during 1999 ...............................................30

10. Simulated total suspended solids yield during water year 1999 by model segment ............................................32

11. Simulated hourly total suspended solids concentrations and observed instantaneous values

for the six calibrated basins during 1999..........................................................................................................33

12. Simulated total nitrogen yield during water year 1999 by model segment ..........................................................35

13. Simulated total phosphorus yield during water year 1999 by model segment .....................................................37

14. Simulated hourly total nitrogen concentrations and observed instantaneous values for the

six calibrated basins during 1999 .....................................................................................................................38

15. Simulated hourly total phosphorus concentrations and observed instantaneous values for the

six calibrated basins during 1999 .....................................................................................................................39

Tables

1. Characteristics of Hydrogeomorphic Regions (HGMRs) on the Delmarva Peninsula within 

the Delaware Inland Bays watershed...................................................................................................................6

2. Land-use categories with number of hectares per watershed model segment ......................................................10

3. Estimated percentage of impervious surface within specific land-use categories,

Sussex County, Delaware..................................................................................................................................11

4. Land-use classes for the watershed simulation with number of hectares per model segment ..............................14

5. Animal count by animal type and model segment ................................................................................................15

6. Factors used to calculate the number of animal units and the number of manure hectares based

on the fraction of time in confinement, by animal type.....................................................................................16

7. Mass of nitrogen and phosphorus generated from manure per animal unit per year by animal type ...................16

8. Fractions of nitrogen and phosphorus lost to runoff or volatilization by animal type ..........................................16

9. Mass fractions of nitrogen and phosphorus species by animal type .....................................................................17

10. Crop goal yields for the five simulated crop types ...............................................................................................17
v

Tables—Continued

11. Plant nutrient composition for the five simulated crop types ...............................................................................17

12. Calculated total annual target nitrogen and phosphorus uptake rates by crop type..............................................18

13. Animal units, manure hectares, and organic fertilizer applications by model segment........................................19

14. Fraction of organic fertilizer application by crop type and month .......................................................................20

15. Modeled planting and harvesting dates by crop type............................................................................................20

16. Monitoring stations used in the analysis of precipitation data..............................................................................21

17. Carbon, nitrogen, and phosphorus constituents with reported units and units required for

Hydrological Simulation Program–FORTRAN calibration and their derivation from reported units..............22

18. U.S. Geological Survey stream-gaging stations used for model calibration ........................................................23

19. Selected land-use classes for hydrologic parameter estimation............................................................................23

20. Goodness-of-fit statistics for comparison of simulated and observed mean daily streamflow

at the six calibration stations for 1999...............................................................................................................26

21. Simulated annual edge-of-stream runoff components for the five single-segment calibrated 

basins during 1999.............................................................................................................................................28

22. Simulated edge-of-stream total suspended solids yields by land-use class for the five singlesegment calibrated basins during water year 1999............................................................................................31

23. Simulated edge-of-stream total nitrogen yields by land-use class for the five single-segment

calibrated basins during water year 1999 ..........................................................................................................34

24. Simulated edge-of-stream total phosphorus yields by land-use class for the five single-segment

calibrated basins during water year 1999 ..........................................................................................................34
vi

Conversion Factors and Abbreviations

_____________________________________________________________________________________________________________________________________

Multiply By To obtain

_____________________________________________________________________________________________________________________________________

Length

millimeter (mm) 0.03937 inch

meter (m) 3.281 foot

kilometer (km) 0.6214 mile

Area

square meter (m2) 0.0002471 acre

hectare (ha) 2.471 acre

 square kilometer (km2) 247.1 acre

hectare (ha) 0.003861 square mile

 square kilometer (km2) 0.3861 square mile

Volume

liter (L) 33.82 ounce, fluid

liter (L) 0.2642 gallon

Flow rate

liter per day(L/d) 0.2642 gallon per day

Mass

kilogram (kg) 2.205 pound avoirdupois

kilogram (kg) 0.001102 ton (T)

Application rate

kilogram per hectare per year [(kg/ha)/yr] 0.8924 pound per acre per year 

_____________________________________________________________________________________________________________________________________

Temperature in degrees Celsius ( °C) may be converted to degrees Fahrenheit ( °F) as follows:

°

F = ( 1.8 x °C ) + 32

Temperature in degrees Fahrenheit ( °F) may be converted to degrees Celsius ( °C) as follows:

°

C = ( °F - 32 ) / 1.8

Concentrations of chemical constituents in water are given either in milligrams per liter (mg/L), millimoles per liter 

(mmol/L), or micromoles per liter (μmol/L).
Abstract 1

Development, Calibration, and Analysis of a Hydrologic and 

Water-Quality Model of the Delaware Inland Bays Watershed

By Angélica L. Gutiérrez-Magness and Jeff P. Raffensperger

Abstract

Excessive nutrients and sediment are among 

the most significant environmental stressors in the 

Delaware Inland Bays (Rehoboth, Indian River, 

and Little Assawoman Bays). Sources of 

nutrients, sediment, and other contaminants within 

the Inland Bays watershed include point-source 

discharges from industries and wastewatertreatment plants, runoff and infiltration to ground 

water from agricultural fields and poultry 

operations, effluent from on-site wastewater 

disposal systems, and atmospheric deposition. To 

determine the most effective restoration methods 

for the Inland Bays, it is necessary to understand 

the relative distribution and contribution of each of 

the possible sources of nutrients, sediment, and 

other contaminants.

A cooperative study involving the Delaware 

Department of Natural Resources and Environmental Control, the Delaware Geological Survey, 

and the U.S. Geological Survey was initiated in 

2000 to develop a hydrologic and water-quality 

model of the Delaware Inland Bays watershed that 

can be used as a water-resources planning and 

management tool. The model code Hydrological 

Simulation Program - FORTRAN (HSPF) was 

used. The 719-square-kilometer watershed was 

divided into 45 model segments, and the model 

was calibrated using streamflow and water-quality 

data for January 1999 through April 2000 from six 

U.S. Geological Survey stream-gaging stations 

within the watershed. Calibration for some 

parameters was accomplished using PEST, a 

model-independent parameter estimator. Model 

parameters were adjusted systematically so that 

the discrepancies between the simulated values 

and the corresponding observations were minimized.

Modeling results indicate that soil and aquifer 

permeability, ditching, dominant land-use class, 

and land-use practices affect the amount of runoff, 

the mechanism or flow path (surface flow, 

interflow, or base flow), and the loads of sediment 

and nutrients. In general, the edge-of-stream total 

suspended solids yields in the Inland Bays 

watershed are low in comparison to yields 

reported for the Eastern Shore from the 

Chesapeake Bay watershed model. The flatness of 

the terrain and the low annual surface runoff are 

important factors in determining the amount of 

detached sediment from the land that is delivered 

to streams. The highest total suspended solids 

yields were found in the southern part of the 

watershed, associated with high total streamflow 

and a high surface runoff component, and related 

to soil and aquifer permeability and land use. 

Nutrient yields from watershed model segments in 

the southern part of the Inland Bays watershed 

were the highest of all calibrated segments, due to 

high runoff and the substantial amount of available 

organic fertilizer (animal waste), which results in 

over-application of organic fertilizer to crops.

Time series of simulated hourly total nitrogen 

concentrations and observed instantaneous values 

indicate a seasonal pattern, with the lowest values 

occurring during the summer and the highest 

during the winter months. Total phosphorus and 

total suspended solids concentrations are 

somewhat less seasonal. During storm events, 

total nitrogen concentrations tend to be diluted and 

total phosphorus concentrations tend to rise 

sharply. Nitrogen is transported mainly in the 

aqueous phase and primarily through ground 

water, whereas phosphorus is strongly associated 

with sediment, which washes off during 

precipitation events.
2 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed

Introduction

Increases in sediment and nutrient loads to coastal bays 

and estuaries in the Chesapeake Bay (Sprague and others, 

2000), Maryland Coastal Bays (Dillow and Greene, 1999), 

and Delaware Inland Bays (Ullman and others, 2002) have 

been attributed to agricultural, domestic, municipal, and 

industrial practices. Within the Delaware Inland Bays watershed (fig. 1a–b), these impacts have been well documented 

by the Delaware Geological Survey (DGS), the Delaware 

Department of Natural Resources and Environmental Control (DNREC), the U.S. Environmental Protection Agency's 

(USEPA) National Estuary Program, the Delaware Center 

for the Inland Bays, the University of Delaware, and other 

agencies. Excessive nutrients and sediment are among the 

most significant environmental stressors in the Inland Bays. 

The sources of nutrients, sediment, and other contaminants 

include point-source discharges from industries and wastewater-treatment plants, runoff and infiltration to ground 

water from agricultural fields and poultry operations, effluent from on-site wastewater disposal (septic) systems, and 

atmospheric deposition. In addition, the practice of agricultural ditching has further aggravated the environmental conditions in some areas of the Inland Bays watershed. 

To determine the most effective restoration methods for 

the Inland Bays, it is necessary to understand the relative distribution and contribution of each of the potential sources of 

nutrients, sediment, and other contaminants. It is also 

important to understand the hydrology of the Inland Bays 

watershed, because the loads (masses of chemical constituents delivered to a water body over a specific time period) 

are strongly dependent on the flow volumes and flow paths 

(such as ground-water discharge or overland flow). Understanding the complex interrelations and interactions between 

hydrologic processes and the sources of contaminants is a 

prerequisite to effective restoration.

A cooperative study involving DNREC, DGS, and the 

U.S. Geological Survey (USGS) was initiated in 2000 to 

develop a hydrologic and water-quality model of the 

Delaware Inland Bays watershed that can be used as a waterresources planning and management tool. The water-quality 

constituents of concern are suspended solids and nutrients 

(nitrogen and phosphorus). A well-documented model code, 

Hydrological Simulation Program-FORTRAN (HSPF) 

(Donigian and others, 1995; Bicknell and others, 1996), was 

used to develop the site-specific model of the Inland Bays 

watershed. A major goal in developing a watershed model 

for the Delaware Inland Bays was to allow prediction of 

loads.
Introduction 3

 
4 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed

Purpose and Scope

The purpose of this report is to (1) document the development and structure of the Inland Bays watershed model of 

streamflow, sediment, and nutrient loading, (2) present the 

methods for model calibration and the results of the calibration, and (3) provide findings and analysis of the model 

results and implications for the understanding of hydrologic 

and nutrient processing functions in the Inland Bays watershed. Hydrologic, agricultural, meteorological, and waterquality data were compiled for 1998 through 2000, and used 

for the development and calibration of the model. The 719-

square-kilometer (km2) watershed was divided into 45 

model segments and the model was calibrated using streamflow and water-quality data for water year 1999 A and part of 

water year 2000 (October 1998 through April 2000) from six 

USGS stream-gaging stations within the watershed. The 

watershed model segmentation was based on several factors 

including the location of impaired streams in the Inland Bays 

watershed listed in the 303(d) list for 1998 from the State of 

Delaware (Delaware Department of Natural Resources and 

Environmental Control, 1998), the location of USGS streamgaging stations and water-quality monitoring stations, and 

the location of point sources. Calibration for some parameters was accomplished using PEST, a model-independent 

parameter estimator (Doherty, 2000). Model parameters 

were adjusted systematically so that the discrepancies 

between the simulated values and the corresponding observations were minimized.

Previous Investigations

Nutrient contamination of ground water and surface 

water in the Inland Bays watershed has been studied for 

decades. Nitrate contamination in the surficial sediments 

has been documented in several previous studies (Miller, 

1972; Robertson, 1977; Denver, 1989; Andres, 1991;

Hamilton and others, 1993). Elevated concentrations of 

nitrate were found in surface water, especially in welldrained watersheds associated with agricultural land use 

(Phillips and Bachman, 1996). Base-flow nitrate concentrations in surface water have been attributed to the discharge 

of shallow ground water (Shedlock and others, 1999). Concentrations of nitrate in ground water were highest in sandy 

soils underlying well-drained agricultural fields where poultry manure and inorganic fertilizer were applied, and lowest 

where soils were poorly drained and dissolved oxygen was 

absent. Concentrations in surface water follow similar patterns, although other processes (such as biological uptake 

and denitrification) in stream channels can also affect nutrient concentrations in surface water. Nitrate concentrations 

in ground water and surface water have been attributed in 

part to on-site wastewater disposal systems and confined animal feeding operations.

Phosphorus is not commonly present in ground water at 

elevated concentrations, but is present in high concentrations 

on soil particles, especially in areas where poultry manure 

has been applied to agricultural fields (Sims and Wolf, 

1993). Phosphorus transport is primarily attributed to overland flow that transports sediment with attached phosphorus 

ions.

A regional assessment of ground-water quality in the 

Delmarva Peninsula, which includes the Delaware Inland

Bays, was conducted under the USGS National WaterQuality Assessment (NAWQA) Program (Hamilton and 

others, 1993; Shedlock and others, 1999), using data collected through 1991. Several wells sampled during the study 

were in the Inland Bays watershed. The results indicate that 

the chemical character of water in the surficial sediments is 

affected by agricultural activities over most of the Delmarva 

Peninsula. The surficial sediments contain large volumes of 

ground water with elevated concentrations of nitrate in 

nearly all areas of the peninsula. Hydrogeomorphic Regions 

(HGMRs) that describe different physical settings with characteristic patterns of ground-water flow and water quality 

were delineated for the Delmarva Peninsula on the basis of 

geologic and geomorphic features, drainage patterns, soil 

types, and land-use patterns (Hamilton and others, 1993) 

(fig. 1a). The Inland Bays watershed includes four of these 

regions: (1) a poorly drained upland unit at the western 

edge of the watershed; (2) a well-drained upland unit covering most of the northern and central parts of the watershed; 

(3) a surficial confined region in the southern part; and (4) a 

unit described as “Others” (beaches, tidal marshes, lagoons, 

and barrier islands) that covers the part of the watershed 

close to the Atlantic Coast and immediately surrounding the 

Inland Bays themselves. The potential effect on nutrient 

transport and transformation in each HGMR is related to differences in soil characteristics and aquifer configuration that 

determine the movement of water and the potential for oxidation and reduction in the aquifer and streams.

A cooperative study between DNREC, the University of 

Delaware College of Marine Studies and DGS began in 1998 

to collect water samples from six streams discharging to the 

Inland Bays during base-flow and storm-event conditions 

(Ullman and others, 2002). The water samples were analyzed for nutrients and total suspended solids (TSS). 

Streamflow data also were collected at the sites. Streamflow, 

nutrient and total suspended solids concentration data were 

used to determine annual and seasonal base-flow and stormevent loads and yields (load per unit watershed area). 

Although no simple statistical relation between land use or 

land cover and the estimated loads or yields was found, the 

data resulting from the project provide information that is 

critical to the understanding of nutrient and sediment loading 

within the Inland Bays watershed.

A. Water year 1999 is from October 1, 1998 through September 30, 1999.
Introduction 5

Acknowledgments

The authors gratefully acknowledge the assistance of 

Richard Greene and Hassan Mirsajadi (Delaware Department of Natural Resources and Environmental Control), 

Scott Andres (Delaware Geological Survey), William Ullman and Joseph Scudlark (University of Delaware), Richard 

McCuen and Ken Staver (University of Maryland), and Kent 

Price (Center for the Inland Bays) who provided information 

on land use/land cover, fertilizer and manure application 

rates, animal population statistics, and feedback on the 

model results and analysis. John Doherty (Watermark 

Numerical Computing) provided assistance with the PEST 

software. The authors also wish to acknowledge Joseph 

Vrabel and Sarah Martucci of the USGS for their technical 

expertise in compiling spatial data and providing graphical 

post-processing of model results; Valerie Gaine for editorial 

insight, Timothy Auer for his work on illustrations, and 

Donna Knight for report layout.

Description of the Study Area

The Inland Bays watershed encompasses approximately 

803 km2 in southeastern Sussex County, Delaware. The 

bays are 84 km2 and the remaining 719 km2 is land. Several 

major and many smaller streams drain to the three bays 

(Rehoboth, Indian River, and Little Assawoman; fig. 1b). 

Land use/cover in the watershed, based on 1997 estimates, is 

32 percent agriculture (including crops, orchard, and pasture), 21.5 percent forest (including brush), 30 percent water 

(including the bays, wetlands, and barren areas), 14.3 percent residential (including low-, medium-, and high-density), 

and 2.2 percent urban (institutional/government, industrial, 

and commercial land uses) (Delaware Office of State Planning Coordination, 2002).

Climate The climate of the region is humid-continental 

with four distinct seasons, which are moderated by the proximity of the Atlantic Ocean. The area receives average 

annual precipitation of 1,110 millimeters (mm), of which 

approximately 400 mm may recharge the unconfined aquifer, although this amount varies spatially and annually 

(Johnston, 1976). The prevailing direction of storms is from 

the west-northwest from November through April, and it 

shifts to the south during May through September. The fall, 

winter, and early spring storms tend to be of longer duration 

and lower intensity than the summer storms. During summer, convective uplift may produce storms that occur during 

the late afternoon and early evening, characterized by scattered high-intensity storm cells that may produce significant 

amounts of rain in a short time span. On the basis of 

National Weather Service (NWS) data, thunderstorms occur 

approximately 30 days per year, with the majority occurring 

from May through August.

Hydrology, Soils, and Topography Indian River Bay, 

Rehoboth Bay, and Little Assawoman Bay are inland bays 

that are protected by a narrow barrier island located between 

the bays and the Atlantic Ocean (fig. 1b). Indian River Bay 

and Rehoboth Bay are connected by a shallow channel; 

Indian River Bay and Little Assawoman Bay are connected 

by a canal. A narrow passageway—the Indian River Inlet—

connects the bays and the ocean.

The western part of the Inland Bays watershed is drained 

by the Indian River. A millpond dam at the west end of 

Indian River Bay separates the tidal and nontidal reaches of 

the Indian River. The northern part of the watershed is 

drained by several small streams. The southern part of the 

watershed is dominated by poorly drained soils and extensive networks of drainage ditches have been constructed to 

promote drainage for agriculture. Throughout the watershed, precipitation recharges the unconfined aquifer, which 

provides ground-water discharge to the streams (referred to 

as base flow) and directly to the bays and at the eastern margin of the watershed, to the ocean.

The study area is located in the Atlantic Coastal Plain 

Physiographic Province. The Coastal Plain is underlain by a 

seaward-dipping wedge of unconsolidated to semiconsolidated marine and nonmarine sediments composed of gravel, 

sand, silt, and clay. In the Inland Bays watershed, the uppermost Coastal Plain sediments form an unconfined aquifer 

that is referred to as the Columbia aquifer (Bachman and 

Wilson, 1984). The primary units that constitute the 

Columbia aquifer in Sussex County are the Beaverdam and 

Omar Formations of Pliocene to Pleistocene age (Andres, 

1987; Talley, 1988; Delaware Geological Survey, 2003). 

The Beaverdam Formation is a medium to coarse quartz 

sand with variable amounts of fine sand and gravel, and 

ranges from 18 to 37 m (meters) thick in eastern Sussex 

County. It is overlain in the southern part of the County by 

the Omar Formation, which consists of alternating beds of 

sand and silt. The Omar Formation was deposited in a backbarrier lagoon environment and has an average thickness of 

14 m in the study area. Thick, discontinuous layers of clay 

and silt in the Omar Formation result in confined or semiconfined aquifer conditions. The sediments that underlie the 

Inland Bays include estuarine, lagoon, and barrier island 

materials that may reach 46 m in thickness in buried stream 

channels. All of these sediments are underlain by many tens 

of hundreds of meters of older Coastal Plain sediments.

The HGMRs defined in the study area (fig. 1a, table 1) 

range from the well-drained uplands with soils with relatively low organic matter content in the east and north, to 

less permeable, more organic-rich and poorly drained areas 

in the western and southern parts of the watershed (fig. 2). 

The central-northern part of the watershed is dominated by 

permeable sandy and sandy loam soils that are well drained. 

The southern part of the study area, which corresponds 

approximately to the surficial confined HGMR shown in figure 1a, is a more poorly drained region with higher organic 

matter content (fig. 2).

Topography in the Inland Bays watershed is flat, typical 

of the Atlantic Coastal Plain Physiographic Province. The 

altitudes in the watershed range from 0 to 22.9 m above sea 

level with a mean of 6.9 m above sea level, on the basis of 

30-m Digital Elevation Model (DEM) data (University of 

Delaware Spatial Analysis Lab, 2003). Slopes in the watershed are generally very gradual. Streams in the uplands may 
6 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed

 

be incised, especially in the well-drained upland HGMR. 

The land surface in the surficial confined HGMR (fig. 1a) is 

extremely flat.

Water Use In 1995, total freshwater withdrawals in Sussex County were estimated to be 3.52 x108 liters per day 

(L/d), or about 12 percent of the freshwater withdrawals in 

the State (Wheeler, 1999). Nearly 90 percent of the estimated total freshwater withdrawals in Sussex County were 

ground water used by industries and for irrigation. Public 

water suppliers in Sussex County relied solely on groundwater sources and withdrew 4.16 x107 L/d. Another 

1.27 x107 L/d were withdrawn for livestock use. 

Model Development

A modeling framework for the watershed was developed 

to provide load estimates for a hydrodynamic and waterquality model of the Inland Bays, and to provide a tool for 

managers and planners to estimate the effects of various 

growth and management scenarios on water quality. The 

modeling framework consists of a set of input files with calibrated parameter values for use with HSPF.

Overview of the Hydrological Simulation Program-FORTRAN 

(HSPF)

The HSPF model simulates flow, sediment transport, 

temperature variations, and water-quality processes over the 

entire hydrologic cycle. Processes controlling water flow 

and chemical constituent concentrations can be represented 

at various levels of detail using HSPF, and simulated for land 

and in-stream (river reach, reservoir) environments. These 

choices are made by specifying the HSPF modules and code 

compartments (Donigian and others, 1995) that are used, and 

the choices subsequently establish the model structure used 

for any one situation. In addition to the choice of modules 

and code compartments, other types of information must be 

supplied for the HSPF calculations, including model parameters and time series of input data. Time series of input data 

for this application include meteorological data, point 

sources, and atmospheric deposition.

Table 1. Characteristics of Hydrogeomorphic Regions (HGMRs) on the Delmarva Peninsula 

within the Delaware Inland Bays watershed

[Modified from Shedlock and others (1999), table 3; m, meters]

HGMR CHARACTERISTICS

Poorly drained upland • Poorly drained forested areas containing wetlands are interspersed with moderately well

to well-drained agricultural areas.

• Streams flow through shallowly incised valleys with low gradients. Ditching to promote 

soil drainage is common in drainage headwaters.

• Water table generally within 3 m of land surface.

• Poor drainage is related to shallow stream incision and high water table, not to finegrained sediments.

Well-drained upland • Relatively flat to gently rolling with a high degree of stream incision.

• Nontidal streams are mostly short, steep tributaries that drain the narrow interfluves 

between tidal rivers.

• Most of the upland area is used for agriculture.

• Wooded areas are generally confined to narrow riparian zones.

• Depth to the water table ranges from 3 to 9 m below land surface beneath topographic 

highs to land surface in riparian discharge areas.

Surficial confined • Stream incision is shallow and ditching to promote soil drainage is widespread.

• The complex set of fine-grained sediments acts as a confining bed over much of the 

region.

• The water table is generally less than 3 m below land surface and occurs in the upper 

sand unit.

Others • Unvegetated areas such as beaches, tidal wetlands, and barrier islands.
Model Development 7
8 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed

Two distinct sets of processes are represented in HSPF: 

(1) processes that determine the fate and transport of water 

and chemical constituents at or below the land surface for 

pervious (HSPF module PERLND) and impervious (HSPF 

module IMPLND) areas; and (2) in-stream processes (HSPF 

module RCHRES). The first step in the modeling process is 

to subdivide a watershed into land segments. The boundaries of the segments are established according to the modeler's needs, but generally, a segment is defined as an area 

with similar hydrologic characteristics. For modeling purposes, water, sediment, and water-quality constituents leaving each segment move laterally to a downslope land 

segment or to a reach or reservoir. For this project, the 

NAWQA data and HGMRs provide a background and 

framework for watershed model development and spatial 

extrapolation of watershed characteristics and model parameter values.

Within a model segment, multiple land-use types can be 

simulated, each using different modules and different model 

parameters. HSPF is a lumped model that does not take into 

account spatial variation, and simulates the water mass balance within land areas as a series of storages with flows 

between the storages determined by empirical (constitutive) 

relations.

Simulated loads from land or watershed processes before 

they reach the stream are known as “edge-of-stream” loads. 

In terms of simulation, all processes are computed for a spatial unit of 1 acre B. The number of acres of each land use in 

a given model segment multiplied by the edge-of-stream 

values (fluxes, loads) computed for the corresponding area 

provide the total edge-of-stream load for the land part of the 

watershed model segment.

The RCHRES module is used to simulate in-stream processes in either a river reach or reservoir (such as flow, sediment transport, water temperature variations, and water 

quality) that affect the delivery of water and solutes from the 

edge of the stream to another body of water. HSPF models 

the flow through a reach or reservoir as unidirectional, with 

constituents that are uniformly dispersed in the water body 

moving at the same horizontal velocity as the water. The 

inflow and outflow of materials are based on a mass balance. 

HSPF uses a convex-routing method to move mass within 

the reach. Outflow may leave the reach in one of three ways 

(irrigation, municipal and industrial water use, or flow to a 

downstream reach), and the processes in the reach will be 

influenced by precipitation, evaporation, and other fluxes.

Stream geometry in the model is represented as a set of 

functional relations between two or more variables. This 

information is entered into the model in the form of a table 

(referred to as an F-table) of reach or reservoir depth, surface 

area, volume, and volume-dependent discharge. The information contained within the F-tables and the convex-routing 

physical parameters control the routing of water within the 

reach or reservoir.

Model Assumptions

A number of assumptions and other decisions were made 

in modeling the Inland Bays watershed. The spatial distribution of precipitation was estimated from meteorological stations at Lewes, Georgetown, and Selbyville, Delaware. 

Agricultural information such as crop type was estimated 

from the Delaware Office of State Planning Coordination 

(DOSPC) land-use data (Delaware Office of State Planning 

Coordination, 2002) and the 1997 Census of Agriculture 

Data (U.S. Department of Agriculture: National Agricultural Statistics Service, 1997a). Nutrient application rates 

were derived from information on animal counts in the 

watershed provided by DNREC in the form of geographic 

information system (GIS) spatial datasets and overlain on the 

model segmentation. Ditching in the southern part of the 

watershed was not taken into consideration when calculating 

the length of the stream to be simulated because of model 

limitations. Although the model simulation is performed on 

a temporal basis, land-use information was not assumed to 

change with time.

Watershed Segmentation

The watershed model segmentation was based on several 

factors including the location of impaired streams in the 

Inland Bays watershed listed in the 303(d) list for 1998 from 

the State of Delaware (Delaware Department of Natural 

Resources and Environmental Control, 1998), the location of 

stream-gaging stations and water-quality monitoring stations, and the location of point sources. Section 303(d) of 

the 1972 Clean Water Act (U.S. Environmental Protection 

Agency, 2003) requires states to develop a list of water bodies that need additional pollution reduction beyond that provided by the application of existing conventional controls. 

The overall objective of a Total Maximum Daily Load 

(TMDL) is to determine the pollutants causing water-quality 

impairments, to identify the maximum permissible load 

capacity for the impaired water body, and to assign load allocation for each pollutant. On the basis of these factors, the 

watershed was divided into 45 segments, with segment areas 

ranging from 1.3 to 53 km2 (fig. 3). The sub-basin draining 

to the Millsboro Pond Outlet stream-gaging station was 

divided into a single network of 12 segments to provide better resolution for the allocation of loads to the listed impaired 

streams.

Land Use

Land-use information was derived from the 1997 

DOSPC land use/land cover data (Delaware Office of State 

Planning Coordination, 2002). The hectares of each land 

use within each model segment are shown in table 2. The 

DOSPC categories were aggregated into a broader classification as follows: (1) forest, wetland, barren, and brush categories were aggregated into a “forest” classification; (2) crop 

and orchard categories were aggregated into “crops;” 

(3) the pasture category was termed “pasture;” and (4) low-, 

B. Although the simulations were set to operate on a per-acre basis, hectares (ha) will be the unit for area used in this report. One hectare is equal to 104

square meters (m2) or 2.471 acres.
Model Development 9
10 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed

 

Table 2. Land-use categories with number of hectares per watershed model segment

[Estimates are for 1997; values from Delaware Office of State Planning Coordination (2002)]

SegmentWaterForestWetlandBarrenBrushCropsOrchardPastureLow-densityresidentialMedium-densityresidentialHigh-densityresidentialInstitutionalIndustrialCommercialTOTAL

010 0.0 6.2 4.3 0.0 0.0 35.6 0.0 0.0 45.9 0.0 10.4 0.0 4.2 26.4 133

020 95.2 165.6 306.9 44.6 35.0 318.9 0.0 0.0 630.8 0.0 217.7 8.0 41.1 71.6 1,936

030 0.2 613.4 84.1 3.8 7.4 778.6 0.0 6.8 110.3 6.5 0.0 0.0 7.9 0.0 1,619

040 62.1 617.9 205.6 46.8 0.8 1,094.6 0.0 32.7 295.6 4.0 50.6 0.0 0.0 4.8 2,416

050 0.8 908.2 154.7 5.7 90.6 801.7 0.0 0.0 252.5 2.3 0.0 0.0 15.6 0.0 2,232

060 58.4 613.0 412.6 88.2 5.2 462.8 0.0 7.6 313.3 0.0 151.4 0.0 0.0 0.0 2,112

070 0.0 395.4 73.9 1.5 43.8 729.7 0.0 5.3 55.8 2.1 28.2 0.0 9.0 0.0 1,345

080 0.3 254.3 36.8 16.3 9.3 363.4 0.0 0.0 35.2 0.0 21.4 0.0 3.6 0.0 741

090 6.4 127.7 30.9 2.8 0.7 110.6 0.0 0.0 119.2 0.0 14.9 0.0 0.0 0.0 413

100 31.4 565.7 113.1 162.9 113.8 588.6 0.0 14.2 204.5 3.2 134.5 0.0 20.0 21.8 1,974

110 37.6 61.2 191.5 20.2 12.5 66.2 0.0 9.3 7.3 0.0 129.4 0.0 0.0 5.2 541

120 122.1 801.1 338.0 59.3 41.0 921.1 0.0 16.8 416.4 8.3 534.7 0.0 9.6 39.2 3,308

130 0.6 706.7 15.2 1.9 94.1 256.3 0.0 0.0 59.1 2.0 34.4 0.0 4.9 0.0 1,175

140 14.1 997.7 244.8 10.3 42.9 572.0 0.0 5.5 184.7 17.2 5.3 0.0 10.8 0.6 2,106

150 1.7 418.0 71.7 6.4 35.8 209.6 7.0 0.0 123.8 3.8 13.7 0.0 193.1 3.3 1,088

160 5.4 197.2 169.5 28.1 48.8 291.8 0.0 11.0 168.4 10.5 20.5 11.7 16.6 25.6 1,005

170 15.4 155.1 237.9 20.0 0.5 622.8 0.0 0.0 124.2 20.0 0.0 1.5 32.3 31.5 1,261

180 17.5 373.9 67.8 6.8 9.2 539.1 0.0 2.8 111.0 14.3 23.8 2.3 12.7 0.0 1,181

190 14.9 88.5 65.1 1.2 1.6 501.4 0.0 0.0 116.2 7.6 15.0 33.1 6.2 24.8 876

200 3.9 491.3 410.4 18.5 27.5 969.0 0.0 5.2 66.6 32.7 8.2 0.0 3.2 0.0 2,037

210 25.2 859.0 157.5 9.0 25.2 593.2 0.0 0.0 73.8 21.2 15.8 0.0 6.7 0.0 1,787

220 2.9 387.3 278.6 12.2 40.7 545.3 0.0 0.7 82.3 16.1 22.9 0.0 5.7 0.0 1,395

230 11.6 241.4 25.9 6.5 5.5 423.6 0.0 0.0 31.6 15.3 15.7 0.0 0.0 0.0 777

240 42.6 50.3 27.1 11.8 26.5 208.2 0.0 0.0 85.7 10.8 31.4 0.0 8.4 0.0 503

250 32.3 343.3 69.6 6.4 53.2 897.3 0.0 0.0 33.4 8.7 26.8 0.0 55.2 0.0 1,526

260 12.1 257.5 429.5 11.5 55.9 1,055.2 0.0 3.3 102.0 28.3 10.1 0.0 13.0 10.4 1,989

270 0.7 78.9 487.6 0.0 6.4 795.3 0.0 0.0 27.3 14.9 27.9 0.0 15.5 0.0 1,454

280 43.5 594.5 432.5 112.4 29.3 491.8 0.0 7.3 198.3 34.6 165.1 5.6 127.6 57.2 2,300

290 1.4 149.9 617.6 4.0 25.4 1,057.2 0.0 15.6 61.4 37.6 85.0 10.9 15.7 5.7 2,088

300 37.2 766.1 1,884.0 64.0 12.3 2,043.6 0.0 5.5 237.4 90.9 117.6 5.1 33.2 4.4 5,301

310 3.9 131.8 73.3 0.7 6.8 596.8 0.0 2.4 52.4 31.8 2.1 0.0 0.0 0.0 902

320 33.3 552.2 238.6 33.6 17.8 595.1 0.0 29.2 334.1 71.8 66.5 0.0 0.0 0.0 1,972

330 4.7 39.0 42.9 15.3 0.0 446.0 0.0 3.0 64.0 26.8 0.9 0.0 0.8 0.0 643

340 42.1 453.7 352.2 42.9 15.3 730.4 0.0 11.4 588.3 28.1 99.0 0.0 0.0 45.2 2,409

350 31.8 96.1 276.6 29.1 5.5 251.3 0.0 0.0 147.7 3.5 49.9 0.0 15.3 5.9 913

360 9.6 139.6 293.2 33.4 25.7 1,066.3 0.0 17.0 101.9 56.4 29.4 0.0 0.0 0.0 1,773

370 156.2 417.6 661.3 31.9 10.1 1,153.0 0.0 27.0 225.8 62.4 106.4 0.0 0.0 5.2 2,857

380 48.4 4.1 94.9 65.8 0.0 8.3 0.0 0.0 65.0 0.0 20.6 0.0 15.7 29.6 352

390 107.7 118.8 262.4 48.0 64.6 141.7 0.0 0.0 366.1 4.4 107.1 17.7 35.9 30.0 1,304

400 120.1 22.6 460.1 146.6 48.8 0.0 0.0 0.0 48.5 0.0 9.6 0.0 46.4 2.7 905

410 32.8 243.7 325.3 4.4 15.6 259.9 0.0 10.7 74.1 27.2 72.4 0.0 1.5 0.0 1,068

420 235.1 630.6 1,125.3 353.9 121.7 692.7 0.0 21.3 852.7 0.0 171.0 91.8 74.2 160.9 4,531

440 59.0 32.5 44.7 24.7 4.4 0.4 0.0 6.6 300.8 0.0 68.5 0.0 13.8 11.3 567

450 41.7 621.3 121.1 0.0 82.3 696.9 0.0 0.0 95.7 24.3 89.9 58.2 5.5 0.4 1,837

470 18.2 173.0 134.8 31.7 1.5 547.1 0.0 10.2 141.3 41.2 84.0 3.8 25.7 6.9 1,219

TOTAL 1,642 15,963 12,152 1,645 1,321 25,531 7 289 7,832 791 2,910 250 907 631 71,871
Model Development 11

 

medium-, and high-density residential and institutional, 

industrial, and commercial categories were aggregated into 

an “urban” classification (fig. 4). The wetlands category is 

simulated as forest because of HSPF limitations in simulating chemical processes in wetlands.

Although estimates of the percentage of impervious area 

for the urban land-use categories were available (table 3), 

these were modified during calibration for a number of reasons. Because HSPF does not consider the location of the 

impervious areas with respect to the stream, there is no attenuation between the edge of the impervious areas and the 

stream, which is likely to occur wherever the actual flow 

path crosses other land types or re-enters the subsurface. In 

addition, the provided estimates were at the county level and 

not specific to the Inland Bays watershed. The final calibrated values for percentage of effective impervious area 

ranged from 15 to 30 percent throughout the watershed.

The 1997 Census of Agriculture (U.S. Department of 

Agriculture: National Agricultural Statistics Service, 1997a) 

was used to determine crop-type proportions, which were 

assumed to be uniform throughout the county (fig. 5). Similarity in nutrient uptake, tillage practices, and planting time 

were used to derive the final five classifications shown in 

table 4: corn, double crops, full-season soybeans, vegetables, and hay.

Double-crop hectares are simulated as a “composite” 

crop. The term “composite” denotes more than one major 

crop category within the simulated land use. Differences in 

the simulation of agricultural landuse are sometimes related 

to the development of parameters for simulated composite 

crops because of aggregated processes. This aggregation 

would occur because wheat is planted during the fall (after 

the corn or soybeans have been harvested), and grown until 

spring of the following year (before the corn or soybeans are 

planted). Because harvesting is not simulated in the current 

model framework, soil conditions are reset at the beginning 

of each simulation year. This introduces greater problems 

if the resetting date is the beginning of the calendar year 

(January), when the winter crops or wheat are in the middle 

of the growing season. Determining a “composite parameterization” is difficult in this case. The problem can be overcome by basing the simulation on the water year, however, 

which allows for the complete cycle of the double crop 

(planting and harvesting) within the simulation year. In the 

Inland Bays watershed model, soil conditions were reset 

using this approach when crops were not on the ground.

Development of Nutrient Application Rates

Mineral (commercial) and organic (animal waste) fertilizer calculations were based on methodologies developed 

for the Chesapeake Bay watershed model (U.S. Environmental Protection Agency, 1998). Work at the University of 

Maryland Wye Research and Education Center guided modifications to these methodologies (Staver and Brinsfield, 

1998). Nutrient application rates were based on a mass balance between the animal wastes produced within each model 

segment and the expected average crop yield in Sussex 

County, as reported in the 1998 Delaware Agricultural 

Statistics (U.S. Department of Agriculture: National Agricultural Statistics Service, 2003). Mineral fertilizer was 

used to supplement the amount needed for the expected average crop yield when the available organic fertilizer was 

insufficient.

 Animal Counts, Animal Units, and the Manure Land-Use 

Category The development of organic fertilizer application 

rates is based on the number and type of animals in the 

watershed. These data are transformed into “animal units” 

as a means of normalizing the nutrient availability from different animal types. One animal unit is equivalent to the 

amount of waste produced by one beef cow. The Sussex 

Conservation District of the State of Delaware provided animal count information for 1999 (Karin H. Grosz, Sussex 

Conservation District, written commun., 2001). The information was provided in GIS format, which was overlain on 

the model segmentation to allocate the animal numbers to 

the model segments (table 5). These data were used to calculate the amount of animal waste available for application 

to cropland, and to calculate the number of hectares to be 

modeled as a “manure” land use.

“Manure hectares” is a derived land-use category used to 

represent what is susceptible to runoff from confined feeding 

operations, and it represents less than 1 percent of the total 

loads in the Inland Bays watershed. All animal categories 

except poultry were used to calculate manure hectares; poultry manure is applied only to cropland in the simulation. 

The number of manure hectares was determined by dividing 

the number of animals in each model segment by the conversion factors found in table 6 to obtain animal units, multiplying by the fraction of time confined, and dividing by an 

assumed animal density in confined feeding operations (358 

animal units per hectare) (U.S. Environmental Protection 

Agency, 1998).

Table 3. Estimated percentage of impervious 

surface within specific land-use 

categories, Sussex County, Delaware

 [Estimates are for 1997 and were provided by the 

Delaware Department of Natural Resources and 

Environmental Control; the remaining percentage of 

each category is pervious.]

Land use

Estimated

percentage of

impervious

surface

Institutional 35 

Industrial 72 

Commercial 60 

Low-density residential 30 

Medium/high-density residential 65 
12 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed
Model Development 13

 

The number of animals per animal unit for sheep and 

horses was estimated on the basis of an assumed weight of 

59 kg (kilograms) for a sheep and 650 kg for a horse; their 

time of confinement was also estimated. These estimates 

have a relatively minor impact on the overall nutrient production in the model segments where these animals are 

found, because poultry animal units far outnumber those of 

other animals. The calculated manure hectares were subtracted from the pasture land-use category, assuming manure 

is stored and treated through the implementation of control 

programs, and that some of these hectares would revert to 

pasture hectares.

Organic Fertilizer Calculations Animal waste applied to 

cropland was calculated on the assumption that manure was 

stored throughout the year for spring and fall applications; 

for pasture, it was assumed that animal waste is applied 

throughout the year except during the months of December, 

January, and February. As recommended by DNREC and 

the Delaware Inland Bays Scientific and Technical Advisory 

Committee (STAC), the allocation of animal waste to crops 

was based on the assumption that animal waste generated in 

a segment was applied to the crops in the same segment. 

For cases in which land-use records indicated that crops 

were cultivated in a particular segment and organic fertilizer 

was not available for application within that segment, it was 

assumed that mineral fertilizer was applied at the rate recommended by DNREC and the Delaware Inland Bays STAC.

According to the animal population data reported by the 

Sussex Conservation District, 99 percent of the organic fertilizer comes from poultry waste and less than 1 percent is 

derived from the waste of other animals. As recommended 

by the Delaware Inland Bays STAC, poultry was assumed to 

be a broiler type for the nutrient calculations. The count 

was defined in terms of animal units using values from table 

6, and the poultry waste was applied to cropland, following 

the assumption that the animals were always confined.

The amounts of nutrients from manure generated within 

each model segment were then expressed as a mass of nitrogen and phosphorus per animal unit as excreted (table 7). 

The calculated amounts of nutrients generated within each 

model segment were reduced by the runoff and volatilization 

fractions (table 8) to obtain the amounts of nitrogen and 

phosphorus available for application to pasture and cropland. 

These amounts were then multiplied by the mass fractions of 

individual nitrogen and phosphorus species (table 9) to 

derive the masses of the forms of nitrogen and phosphorus 

simulated by HSPF. For animal waste, these forms include: 

(1) ammonia (adsorbed and dissolved); (2) organic nitrogen; 

(3) orthophosphate (adsorbed and dissolved); and (4) organic 

phosphorus.

Nutrient Requirements and Goal Yields The “nutrient 

requirement” is the amount of fertilizer that a farmer applies 

and expects to be used by the crops during their growing 

cycle. The “goal yield” refers to a representative or reference yield under normal conditions; the actual yield of the 

crop, however, will increase or decrease from year to year 

based on growing conditions in the area. The goal yields 

were used in the model to establish the nutrient application 

amounts.

Crop goal yields (table 10) for corn, double crops, and 

full-season soybeans are the average of reported yields for 

Sussex County, Delaware (U.S. Department of Agriculture: 

National Agricultural Statistics Service, 2003) from 1995 

through 1999. In the case of double crops, reported yields 

from wheat, barley, and soybeans were averaged from 1995 

through 1999 to obtain the goal yield. Goal yields for hay 

and vegetables are values reported for 1999. Because the 

potatoes category is the largest reported vegetable crop in 

Sussex County, the reported yield for potatoes for 1999 was 

used as the goal yield for the vegetables land-use class.

Plant composition values are shown in table 11 (Lander 

and others, 1998). This information was used to calculate 

the total annual target for plant uptake of nitrogen and phosphorus for all soil layers during a simulated year (table 12). 

The plant uptake rate for potatoes was used as the uptake for 

the vegetables land-use class.

Total Nutrient Applications The total nutrient applications were based on the type of crop and the crop nutrient 

requirements. In the case of full-season soybeans, nitrogen 

fixation was simulated, and phosphorus was supplied by 

mineral fertilizer. If organic fertilizer was applied in a specific model segment because of manure generation in that 

segment, then phosphorus in the mineral form was not 

applied.
14 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed

 

Table 4. Land-use classes for the watershed simulation with number of hectares per model segment Segment Corn Double crops Full-season soybeans Vegetables Hay Forest Pasture Pervious urban Impervious urban TOTAL

 010 11.3 6.8 14.3 3.0 0.2 10.5 0.0 78.9 8.1 133

020 101.6 61.0 127.7 26.7 2.0 552.3 0.0 678.4 290.7 1,840

030 248.0 148.8 311.8 65.2 4.9 708.7 6.8 87.3 37.4 1,619

040 348.6 209.2 438.3 91.6 6.9 871.2 32.7 248.5 106.5 2,354

050 255.3 153.2 321.0 67.1 5.1 1,159.3 0.0 189.3 81.1 2,231

060 147.4 88.4 185.3 38.7 2.9 1,119.0 7.6 325.2 139.4 2,054

070 232.4 139.4 292.2 61.1 4.6 514.7 5.3 66.6 28.5 1,345

080 115.7 69.4 145.5 30.4 2.3 316.8 0.0 42.2 18.1 740

090 35.2 21.1 44.3 9.3 0.7 162.1 0.0 93.9 40.2 407

100 187.5 112.5 235.7 49.3 3.7 955.4 14.2 268.8 115.2 1,942

110 21.1 12.7 26.5 5.5 0.4 285.5 9.3 99.3 42.6 503

120 293.4 176.0 368.8 77.1 5.8 1,239.4 16.8 705.8 302.5 3,186

130 81.6 49.0 102.6 21.5 1.6 817.9 0.0 90.3 10.0 1,175

140 182.2 109.3 229.0 47.9 3.6 1,295.7 5.5 153.0 65.6 2,092

150 69.0 41.4 86.7 18.1 1.4 531.9 0.0 236.4 101.3 1,086

160 92.9 55.8 116.8 24.4 1.8 443.6 11.0 177.3 76.0 1,000

170 198.4 119.0 249.4 52.1 3.9 413.5 0.0 146.6 62.8 1,246

180 171.7 103.0 215.9 45.1 3.4 457.7 2.8 114.9 49.2 1,164

190 159.7 95.8 200.8 42.0 3.2 156.3 0.0 142.1 60.9 861

200 308.6 185.2 388.0 81.1 6.1 947.7 5.2 77.5 33.2 2,033

210 188.9 113.4 237.5 49.7 3.7 1,050.8 0.0 82.3 35.3 1,762

220 173.7 104.2 218.3 45.6 3.4 718.8 0.7 88.9 38.1 1,392

230 134.9 81.0 169.6 35.5 2.7 279.3 0.0 43.8 18.8 766

240 66.3 39.8 83.4 17.4 1.3 115.7 0.0 95.4 40.9 460

250 285.8 171.5 359.3 75.1 5.7 472.6 0.0 86.9 37.2 1,494

260 336.1 201.6 422.5 88.3 6.6 754.4 3.3 114.7 49.1 1,977

270 253.3 152.0 318.4 66.6 5.0 572.9 0.0 59.9 25.7 1,454

280 156.6 94.0 196.9 41.2 3.1 1,168.7 7.3 411.8 176.5 2,256

290 336.7 202.0 423.3 88.5 6.7 796.9 15.6 151.5 64.9 2,086

300 650.9 390.5 818.3 171.1 12.9 2,726.5 5.5 342.0 146.6 5,264

310 190.1 114.0 238.9 49.9 3.8 212.6 2.4 60.8 25.7 898

320 189.5 113.7 238.3 49.8 3.7 842.1 29.2 330.7 141.7 1,939

330 142.1 85.2 178.6 37.3 2.8 97.2 3.0 70.9 21.6 639

340 232.6 139.6 292.5 61.1 4.6 864.1 11.4 532.4 228.2 2,367

350 80.0 48.0 100.6 21.0 1.6 407.4 0.0 155.6 66.7 881

360 339.6 203.8 426.9 89.2 6.7 491.9 17.0 131.4 56.3 1,763

370 367.2 220.3 461.7 96.5 7.3 1,121.0 27.0 279.8 119.9 2,701

380 2.7 1.6 3.3 0.7 0.1 164.8 0.0 91.7 39.3 304

390 45.1 27.1 56.7 11.9 0.9 493.9 0.0 392.8 168.4 1,197

400 0.0 0.0 0.0 0.0 0.0 678.2 0.0 75.1 32.2 785

410 82.8 49.7 104.1 21.8 1.6 589.0 10.7 122.6 52.5 1,035

420 220.6 132.4 277.4 58.0 4.4 2,231.5 21.3 945.4 405.2 4,296

440 0.1 0.1 0.2 0.0 0.0 106.2 6.6 276.1 118.3 508

450 222.0 133.2 279.0 58.3 4.4 824.7 0.0 191.8 82.2 1,796

470 174.3 104.6 219.1 45.8 3.4 341.0 10.2 212.1 90.9 1,201

TOTAL 8,134 4,880 10,225 2,137 161 31,081 289 9,369 3,952 70,228
Model Development 15

 

Table 5. Animal count by animal type and model segment

[Provided by Karin H. Grosz, Sussex Conservation District, written commun., 2001]

 Segment Beef cattle Dairy cattle Swine Horses Sheep Poultry 1

010 0 0 0 0 0 0

020 0 0 0 0 0 0

030 50 0 0 0 0 273,800

040 100 0 0 24 0 185,600

050 0 0 0 0 0 56,000

060 0 0 0 0 0 0

070 0 0 0 0 0 0

080 41 0 0 0 0 0

090 39 0 0 0 0 0

100 0 0 0 0 0 32,000

110 0 0 0 0 0 0

120 0 0 0 0 20 80,000

130 0 0 0 0 0 0

140 20 0 0 0 0 305,000

150 0 0 0 0 0 36,000

160 0 0 0 0 0 186,200

170 0 0 0 0 0 379,000

180 0 0 0 0 0 366,900

190 0 0 0 0 0 230,000

200 0 0 0 0 0 289,667

210 0 0 0 0 0 248,200

220 0 0 0 0 0 278,900

230 0 0 0 0 0 228,500

240 0 0 0 0 0 318,000

250 0 0 0 0 0 131,000

260 0 0 0 0 0 403,800

270 0 0 200 0 0 294,000

280 0 0 1,050 0 0 478,000

290 0 0 0 0 0 475,100

300 0 0 1,536 0 0 1,464,500

310 0 0 0 0 0 402,000

320 0 0 100 0 0 1,207,600

330 0 0 0 0 0 441,000

340 0 0 0 50 0 318,000

350 0 0 0 0 0 32,000

360 0 0 200 0 0 1,129,200

370 0 0 0 0 0 809,800

380 0 0 0 0 0 0

390 0 0 0 0 0 54,000

400 0 0 0 0 0 0

410 0 0 0 0 0 282,000

420 0 150 0 0 0 0

440 0 0 0 0 0 0

450 0 0 0 0 0 431,800

470 130 0 0 0 0 1,004,000

 TOTAL 380 150 3,086 74 20 12,851,567

1 For this study, poultry was assumed to be a “Broiler” type.
16 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed

ERRATA SHEET REVISED 3-10-2006 TO REPLACE PAGE 16

 

Table 6. Factors used to calculate the number of 

animal units and the number of manure 

hectares based on the fraction of time 

in confinement, by animal type

Animal

type

Animals/

animal

unit

Fraction

of time

confined

Fraction

of time

unconfined

Beef cattle 1.0 0.2 0.8

Dairy cattle 0.71 0.8 0.2

Swine 2.7 1.0 0.0

Sheep 7.7 0.5 0.5

Horses 0.7 0.5 0.5

Poultry 455 1.0 0.0 Table 7. Mass of nitrogen and phosphorus 

generated from manure per animal unit 

per year by animal type

 [Poultry values are based on capacity, assuming 6.0 

flocks per year; values in parentheses indicate per flock 

values; values from U.S. Environmental Protection 

Agency (1998) and U.S. Department of Agriculture: 

Natural Resources Conservation Service (2003)]

Animal

type

Nitrogen per

animal unit

(kilograms

per year)

Phosphorus

per animal

unit (kilograms

per year)

Beef cattle 51.3 18.2

Dairy cattle 74.5 11.6

Swine 69.5 26.5

Poultry 182.1 (30.4) 56.5 (9.4)

Sheep 13.2 11.8

Horses 8.6 6.3

 

Table 8. Fractions of nitrogen and phosphorus lost 

to runoff or volatilization by animal type

 [Values from U.S. Environmental Protection Agency (1998)]

Animal type

Fraction volatilized or lost to 

runoff

Nitrogen Phosphorus

Beef cattle, sheep, horses 0.70 0.15

Dairy cattle 0.60 0.15

Swine 0.75 0.15

Poultry 0.40 0.15
Model Development 17

 

 

As suggested by the Delaware Inland Bays STAC, the 

fertilizer application rates were increased by 10 percent of 

the recommended values to account for the over-application 

of fertilizer. The sequence of application within the model 

is as follows:

1. Organic fertilizer is applied to fulfill 110 percent of 

the nutrient requirement for up to 75 percent of the 

corn hectares in the model segment; the remaining 

hectares receive mineral fertilizer.

2. If organic fertilizer remains after application to corn 

hectares, it is applied to fulfill 110 percent of the 

nutrient requirement for up to 10 percent of the

double-crop hectares. The remaining double-crop 

hectares receive mineral fertilizer.

3. If organic fertilizer remains after application to double 

crops, it is applied to fulfill 110 percent of the nutrient requirement for full-season soybeans for up to 

50 percent of the full-season-soybeans hectares. The 

remaining full-season-soybeans hectares will fix 

nitrogen from atmospheric deposition and will 

receive the required phosphorus in the mineral form.

4. If organic fertilizer remains after application to fullseason soybeans, it is applied to fulfill 110 percent of 

the nutrient requirement for vegetables for up to

50 percent of the vegetables hectares. The remaining vegetables hectares receive mineral fertilizer.

5. If organic fertilizer remains after application to vegetables, it is applied to fulfill 110 percent of the nutrient requirement for hay for up to 20 percent of the 

hay hectares. The remaining hay hectares receive 

mineral fertilizer.

6. If organic fertilizer remains, steps 1 through 5 begin 

again, with over-application of organic fertilizer to 

50 percent of the remaining corn hectares receiving 

only mineral fertilizer in the first cycle.

 

Table 9. Mass fractions of nitrogen and 

phosphorus species by animal type

 [Values from U.S. Environmental Protection Agency 

(1998) and Ken Staver, University of Maryland, written 

commun., 2002]

Animal

type

Ammonia Organic

nitrogen

OrthophosphateOrganic

Phosphorus

Beef cattle,

 dairy

 cattle,

 swine,

 sheep,

 horses

0.48 0.52 0.175 0.825

Poultry 0.22 0.78 0.38 0.62

Table 10. Crop goal yields for the five simulated 

crop types

 [Values from U.S. Department of Agriculture: National 

Agricultural Statistics Service (2003); cwt, hundredweight or 100-pound unit]

Crop type Goal yield Units

Corn 275.8 bushels per hectare

Double crops 77.2 bushels per hectare

Full-season

 soybeans

67.6 bushels per hectare

Hay 7.4 tons per hectare

Vegetables 618 cwt per hectare

Table 11. Plant nutrient composition for the five simulated crop types

[Values from Lander and others (1998) ; cwt, hundredweight or 100-pound unit]

Crop type Units Plant composition

(dry matter basis)

Nitrogen Phosphorus

Corn kilograms per bushel 0.36 0.07

Double crops kilograms per bushel 0.41 0.08

Full-season soybeans kilograms per bushel 1.6 0.16

Hay (average between alfalfa hay and small grain hay values) kilograms per ton 17.3 2.1

Vegetables (Irish potatoes) with 77 percent moisture content kilograms per cwt 0.16 0.03
18 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed

 

If the application of organic fertilizer fulfills the phosphorus requirement, but not the nitrogen requirement, then 

nitrogen will be the only mineral applied. If the nutrient 

requirements for nitrogen and phosphorus are not fulfilled by 

the application of organic fertilizer, then the ratio of nitrogen 

to phosphorus in mineral fertilizer is assumed to be 5:1, 

except for applications to double crops, which is assumed to 

be 2.5:1. The results of the calculations of animal units, 

manure hectares, and organic fertilizer applications are 

shown in table 13.

Method of Fertilizer Application The HSPF model only 

allows the simulation of a “broadcast” type fertilizer application, which provides a uniform distribution of nutrients 

within the simulated hectare; therefore, all the fertilizer 

applications were assumed to be of a broadcast type. For 

the application of mineral fertilizer to all crops and organic 

fertilizer to corn and double crops, 10 percent of the application was delivered to the surface layer (first cm, or centimeter, of soil), and the remaining 90 percent was delivered to 

the upper soil layer (next 29 cm of soil). For the application 

of organic fertilizer to the full-season soybeans, hay, and 

vegetables, 50 percent was applied to the surface layer and 

50 percent to the upper soil layer.

Schedule of Organic Fertilizer Application Organic 

fertilizer was applied to specific soil layers according to the 

schedule shown in table 14. For pasture, organic fertilizer 

was applied throughout the year, except during December, 

January, and February.

Schedule of Mineral Fertilizer Application Mineral 

fertilizer was applied according to the following schedule:

 Table 12. Calculated total annual target nitrogen 

and phosphorus uptake rates by crop 

type

Crop type

Total nitrogen

uptake rate

(kilograms per

hectare per

year)

Total

phosphorus

uptake rate

(kilograms per

hectare per year)

Corn 99 19

Double crops 32 6.2

Full-season

 soybeans

108 11

Hay 128 16

Vegetables 99 19

Corn 20 percent of the application

at planting distributed

over 6 days

80 percent of application

30 to 40 days after

planting distributed over

18 days

Double crops 10 percent of nitrogen

application distributed

over 10 days in October

20 percent of nitrogen

application distributed

over 10 days in February

70 percent of nitrogen

application distributed 

over 15 days in March

100 percent of phosphorus

application distributed

over 10 days in October

Full-season soybeans 100 percent of phosphorus

application distributed

over 10 days in May

Hay 50 percent of nitrogen and

phosphorus application

distributed over 12 days

in April

50 percent of nitrogen and

phosphorus application

distributed over 12 days

in July

Vegetables 50 percent of nitrogen and

phosphorus application

distributed over 12 days

in April

50 percent of nitrogen and

phosphorus application

distributed over 12 days

in May

Pervious urban 22.7 kg of nitrogen

distributed between

March and October with

a weekly application
Model Development 19

ERRATA SHEET REVISED 3-10-2006 TO REPLACE PAGE 19

 

Table 13. Animal units, manure hectares, and organic fertilizer applications by model segment

 Segment Animal 

units

Manure

hectares

Kilograms of 

organic fertilizer

applied to crops

Kilograms of

organic fertilizer

applied to pasture

010 0 0.00 0 0

020 0 0.00 0 0

030 652 0.28 8,066,821 391,837

040 542 0.27 5,765,677 951,603

050 123 0.05 1,629,862 0

060 0 0.00 0 0

070 0 0.00 0 0

080 41 0.02 80,327 321,306

090 39 0.02 76,408 305,633

100 70 0.03 931,350 0

110 0 0.00 0 0

120 178 0.08 2,339,801 11,426

130 0 0.00 0 0

140 690 0.29 8,916,112 156,735

150 79 0.03 1,047,769 0

160 409 0.17 5,419,292 0

170 833 0.35 11,030,675 0

180 806 0.34 10,678,508 0

190 505 0.21 6,694,077 0

200 637 0.27 8,430,666 0

210 545 0.23 7,223,782 0

220 613 0.26 8,117,296 0

230 502 0.21 6,650,420 0

240 699 0.29 9,255,289 0

250 288 0.12 3,812,713 0

260 887 0.37 11,752,471 0

270 720 0.48 9,330,103 0

280 1,439 1.53 17,972,003 0

290 1,044 0.44 13,827,634 0

300 3,788 2.94 48,562,955 0

310 884 0.37 11,700,082 0

320 2,691 1.21 35,533,477 0

330 969 0.41 12,835,165 0

340 770 0.39 9,605,143 349,854

350 70 0.03 931,350 0

360 2,556 1.25 33,638,334 0

370 1,780 0.75 23,568,972 0

380 0 0.00 0 0

390 119 0.05 1,571,653 0

400 0 0.00 0 0

410 620 0.26 8,207,520 0

420 211 0.47 2,238,191 559,548

440 0 0.00 0 0

450 949 0.40 12,567,402 0

470 2,337 1.00 29,475,795 1,018,776

 TOTAL 30,088 15.85 389,485,094 4,066,717
20 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed

 

A uniform distribution of fertilizer over 10 days for the 

cropland and 4 days for the pervious urban land in the corresponding month was adopted, because not all farmers within 

a given model segment apply fertilizer on the exact same 

day, and because the applications in the simulation represent 

an average date of application.

Planting and Harvesting Dates Information on planting 

and harvesting times for the State of Delaware was obtained 

from U.S. Department of Agriculture: National Agricultural 

Statistics Service (1997b), which reports “usual” planting 

and harvesting dates, with beginning date, most-active phase 

dates, and end date for many different crops. The “usual” 

planting dates represent the times when crops are usually 

planted in the fields. The “usual” harvesting dates represent 

the periods during which harvest of the crop actually occurs. 

The beginning dates for planting from U.S. Department of 

Agriculture: National Agricultural Statistics Service 

(1997b) were used as the planting dates for nutrient application; the values for the end of the most-active phase of harvesting were used in the model as the harvesting date, or end 

of the period of crop nutrient uptake (table 15).

Atmospheric Deposition

Atmospheric nitrogen deposition data for the HSPF 

model simulations are from Scudlark and Church (2001). 

The application rates for dry and wet deposition are as follows:

Wet flux:

Nitrate = 20 millimoles per liter of rainfall 

(mmol/L);

Ammonium = 17.1 mmol/L;

Organic N = 9.1 mmol/L.

Dry deposition:

Nitrate = 1.08 kilograms of nitrogen per hectare 

per year (kg N/ha/yr);

Ammonium = 0.33 kg N/ha/yr;

Organic N = 0.46 kg N/ha/yr.

 

On-Site Wastewater Disposal System Information

GIS methodologies were used to determine the on-site 

wastewater disposal (septic) system information by model 

segment. The Inland Bays watershed model segmentation 

was overlain on the GIS layer (provided by DNREC) 

containing the on-site wastewater disposal system information to determine the number of on-site wastewater disposal 

systems by model segment. Mean nitrate and orthophosphate edge-of-septic-field loading rates of 0.014 and 

0.0006 kg/day/system, respectively (Maizel and others, 

1997; U.S. Environmental Protection Agency, 1998) were 

used to generate estimated edge-of-stream loads for each 

model segment, which were incorporated into the simulation 

as additions to the edge-of-stream loads. The edge-of-septic-field nitrate loads were attenuated by 65 percent (Maizel 

and others, 1997) to represent volatilization to the atmosphere, denitrification, and other losses. An estimate for 

orthophosphate load attenuation of 95 percent (primarily due 

to soil retention) was used.

Point Sources

Point source information was obtained from DNREC,

who provided data from the Permit Compliance System 

Table 14. Fraction of organic fertilizer application by crop type and month

[–, no fertilizer was applied]

Crop type

Fraction of organic fertilizer applied

March April May September October November December

Corn 0.25 0.25 – 0.10 0.20 0.10 0.10

Double crops 0.10 0.10 – – 0.80 – –

Full-season soybeans 0.40 0.30 0.30 – – – –

Hay 0.40 0.30 0.30 – – – –

Vegetables 0.40 0.30 0.30 – – – –

Table 15. Modeled planting and harvesting dates 

by crop type

Crop type Planting date Harvesting date

Corn April 20 October 15

Double crops, crop 1 June 26 October 5

Double crops, crop 2 October 15 June 12

Full-season soybeans April 28 August 15

Hay May 10 November 19

Vegetables April 15 September 15
Model Development 21

 

(PCS). The PCS is a data-base management system that 

supports the National Pollutant Discharge Elimination 

System (NPDES) regulations. Loads from the municipal 

facility located in Georgetown, Delaware (fig. 3) were incorporated in the simulation because of the location of the 

facility in the nontidal area. Flow and concentrations 

are reported as monthly average values in units of million 

gallons per day (Mgal/d) for flow, and milligrams per liter 

(mg/L) for concentrations. This information was input into 

the model as a load in pounds per day (lb/d) in a time-series 

format for the following constituents: biological oxygen 

demand (BOD), TSS, dissolved oxygen (DO), ammonia, 

nitrate, orthophosphate, and discharge.

Meteorological Data

HSPF simulations are mostly influenced by precipitation; 

therefore, the quality of the simulation will be greatly influenced by the quality of the precipitation data. For the Inland 

Bays watershed model, simulations were run on an hourly 

basis and the period during which the streamflow was 

recorded at the stream-gaging station established the period 

of the calibration; however, the period of simulation was 

extended from January 1998 to April 2000. For the majority 

of the streams in the Inland Bays watershed, this period 

started in the fall of 1998 and ended during the spring of 

2000, with the exception of the basins draining to Millsboro 

Pond Outlet (station number 01484525) and Beaverdam 

Ditch (station number 01484695) for which streamflow 

records are still collected. Daily precipitation data for the 

station located in Lewes, Delaware (fig. 3) were obtained 

from the National Climatic Data Center (National Oceanic 

and Atmospheric Administration, 2001). Hourly precipitation data for the Georgetown, Delaware location were 

obtained from the University of Delaware (N. Dean Dey, 

Research and Education Center, University of Delaware, 

written commun., 2001). Daily precipitation data collected 

at the wastewater treatment plant in Selbyville, Delaware 

were obtained from the Town of Selbyville, Delaware (Scott 

Andres, Delaware Geological Survey, written commun., 

2001). Daily precipitation amounts were allocated using the 

distribution of hourly precipitation at the Georgetown station 

(table 16). To guarantee the complete allocation of the daily 

precipitation, a default allocation of 1/24 (uniform distribution across 24 hours) was used for days in which precipitation did not occur at the Georgetown station.

 Minimum and maximum air temperatures were obtained 

at the Georgetown and Lewes stations and were used to 

derive time series of potential evapotranspiration using the 

Hamon (1961) method. Data for the Georgetown station 

were obtained from the University of Delaware (N. Dean 

Dey, Research and Education Center, University of Delaware, written commun., 2001). For the simulation of snow 

and ice, the following meteorological data were input to the 

simulation in the form of time series: cloud cover, wind 

speed, radiation, and dew point; this information was 

obtained from data developed by the U.S. Environmental 

Protection Agency (1997).

Table 16. Monitoring stations used in the analysis of precipitation data

[NOAA, National Oceanic and Atmospheric Administration; HR, hourly; DY, daily; NA, not applicable]

Agency Data

type 

Station

number

Location

Available

period of

record

Period of

record

used

Segments 

calibrated

Comments

University of

 Delaware

HR 073570 Georgetown, DE 1984 - 2002 1/1998 - 4/2000 130, 450 Used to allocate 

daily into hourly 

precipitation and 

for the simulation 

of the Millsboro 

Pond Outlet basin 

NOAA DY 075320 Lewes, DE 1984 - 2002 1/1998 - 4/2000 010, 030 Data allocated into 

hourly precipitation using proportions from 073570

Town of 

 Selbyville

DY NA Selbyville, DE 1984 - 2002 1/1998 - 4/2000 310, 330 Data allocated into 

hourly precipitation using proportions from 073570
22 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed

Development of Water-Quality Data Base for Model 

Calibration

All water-quality data used for model calibration (including field parameters and laboratory analyses of nitrogen and 

phosphorus species concentrations and TSS concentrations) 

were provided by DNREC. These data are from the Inland 

Bays TMDL data base, version 6.62 (Andres and others, 

2002). All methods used for sample collection, processing, 

preservation, and analysis are described in Ullman and 

others (2002). The constituents analyzed and specified concentration units are shown in table 17. Two additional steps 

were performed to make the data directly comparable with 

HSPF-simulated constituents. The first step was to convert 

concentrations in micromoles per liter (μmol /L) to concentrations in mg/L (as C, N, or P), by multiplying the reported 

values by the atomic weights of carbon (12.011 grams per 

mole, or g/M), nitrogen (14.0067 g/M), or phosphorus 

(30.97376 g/M), and then dividing by 1,000. The second 

step was to derive a number of other quantities, such as total 

nitrogen and total phosphorus, that are necessary for model 

calibration and that were not reported by DNREC. The derivations of these quantities are also shown in table 17.

Model Calibration Approach

Limited initial model calibration was performed using 

PEST, a parameter estimator (Doherty, 2000). Due to the 

brevity of the observation record, only limited parameter 

sensitivity was performed, which for hydrologic parameters 

indicated strong sensitivity dependence on the volume of 

annual runoff (Gutiérrez-Magness and McCuen, 2002). 

Model performance was evaluated for the period January 

through December of 1999. To allow time for the model to 

reach reasonable initial conditions, the simulation was 

started in January of 1998 with arbitrary initial conditions 

and allowed to run for one year. During calibration, these 

initial conditions were manually adjusted to improve the calibration. Simulations were carried out through April of 

2000, which provided a hydrologically contrasting period 

(1999 was a very dry year and the spring of 2000 was relatively wet) for model verification. During calibration of 

TSS and nutrients, manual adjustment of hydrologic parameters was performed to improve the overall model predictions.

Table 17. Carbon, nitrogen, and phosphorus constituents with reported units and units 

 required for Hydrological Simulation Program–FORTRAN calibration and 

 their derivation from reported units

[Derived constituents are in bold; μmol/L, micromoles per liter; mg/L, milligrams per liter; C, carbon; N, nitrogen; P, phosphorus]

Reported or

derived parameter

Symbol

Reported 

concentration

unit

Required

concentration

unit

Derivation

Dissolved Organic Carbon DOC μmol/L mg/L as C

Particulate Organic Carbon POC μmol/L mg/L as C

Total Organic Carbon TOC mg/L as C TOC = POC + DOC

Nitrate + Nitrite NO23 μmol/L mg/L as N

Ammonium NH4 μmol/L mg/L as N

Total Dissolved Nitrogen TDN μmol/L mg/L as N

Particulate Organic Nitrogen PON μmol/L mg/L as N

Dissolved Inorganic Nitrogen DIN mg/L as N DIN = NO23 + NH4

Dissolved Organic Nitrogen DON mg/L as N DON = TDN – DIN

Total Organic Nitrogen TON mg/L as N TON = PON + DON

Total Nitrogen TN mg/L as N TN = PON + TDN

Phosphate PO4 μmol/L mg/L as P

Total Dissolved Phosphorus TDP μmol/L mg/L as P

Particulate Organic Phosphorus POP μmol/L mg/L as P

Dissolved Organic Phosphorus DOP mg/L as P DOP = TDP - PO4

Total Organic Phosphorus TOP mg/L as P TOP = POP + DOP

Total Phosphorus TP mg/L as P TP = TDP + POP
Model Calibration Approach 23

Calibration of Hydrology

Initial model calibration for hydrology was performed 

using PEST (Doherty, 2000), and the observed data for six 

basins with gaged outlets (table 18, fig. 3). Although a 

USGS stream-gaging station is located at the outlet of segment 170, this segment was not calibrated because information was not available about an upstream diversion from a 

gravel facility. The hydrologic calibration was performed 

with the available streamflow records between October 1998 

and April 2000.

Parameter Estimation During the calibration process, the 

largest land-use class in each basin (table 19) was selected 

for parameter estimation because it would have the greatest 

impact on the hydrology. Parameter values for other landuse classes were tied to those estimated by a ratio. HSPF 

allows some of the hydrologic parameters to vary monthly, 

or to remain constant throughout the year. The parameters 

controlling the interception storage capacity and the lower 

zone evapotranspiration (an index to the density of deeprooted vegetation) were allowed to vary monthly during the 

calibration. For these calculations, the maximum and minimum values of the parameter were selected, and included in 

an equation that would describe the annual seasonality of the 

estimated parameter.

Objective Function for Parameter Estimation PEST uses 

nonlinear techniques to estimate optimal parameter values, 

based on a user-determined objective function, which is generally some relation between observed values and model output. A multiple-criterion objective function was used in the 

calibration process. The four criteria are briefly discussed 

below. The objective function used for each calibrated segment was taken as a weighted average of these criteria.

Daily flows Part of the objective function was residuals 

calculated by subtracting model-generated daily flows from 

their measured counterparts. Daily rather than hourly flows 

were used for this purpose because of the potential for timing 

 

errors because the precipitation supplied to the model was 

measured at a rain gage situated at some distance from the 

watershed.

Flow differences Kuczera (1983) suggested that model output consist of a time series in which the entry for a particular 

day consists of the flow measured that day minus part of the 

flow measured on the previous day. This is then matched to 

an observation time series that is calculated in the same way. 

In this study, a similar procedure was undertaken. Using a 

time-series manipulation utility that accompanies the PEST 

software (Doherty, 2000), a time series consisting of the differences between hourly simulated and observed flows was 

calculated. Extensive application of this method during 

model calibration demonstrated that it helped to preserve the 

rapid rise and fall of the stream hydrograph for Swan Creek, 

for example, because the discrepancy between model outputs and field measurements was reduced.

Table 18. U.S. Geological Survey stream-gaging stations used for model calibration 

Station 

number

Station name Segments 

drained Period of record Total area drained

(square kilometers)

01484668 Munchy Branch near Rehoboth Beach, DE 010 August 1998 to September 2000 1.33

01484654 Bundicks Branch at Robinsonville, DE 030 August 1998 to March 2000 16.19

01484534 Swan Creek near Millsboro, DE 130 August 1998 to March 2000 11.75

01484600 Blackwater Creek near Clarkesville, DE 310 October 1998 to March 2000 9.02

01484695 Beaverdam Ditch near Millville, DE 330 August 1998 to September 2002 

 (continuing)

6.43

01484525 Millsboro Pond Outlet at Millsboro, DE 140, 150, 160,

170, 180, 190,

200, 210, 220,

230, 240, 450

May 1986 to September 1988 and

March 1991 to September 2002

 (continuing)

158.53

Table 19. Selected land-use classes for

 hydrologic parameter estimation

Location Land-use class

Munchy Branch Pervious and impervious urban

Bundicks Branch, 

 Blackwater Creek, 

 and Beaverdam Ditch 

Forest

Swan Creek Forest and pervious urban

Millsboro Pond Outlet Forest and corn
24 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed

Monthly volumes Model-calculated and observed monthly 

volumes were used in the calibration process.

Exceedance times Thresholds of specified flow depths 

were used as the probability that an event of specified depth 

will occur during the period of calibration.

Calibration of Total Suspended Solids and Nutrients

Calibration for the simulation of TSS was performed 

manually, taking into consideration the reduction of erosion 

achieved by the use of best management practices. Parameters related to the edge-of-stream loads were set based on 

HGMR, soils information, and a visual comparison of the 

simulated and observed in-stream concentrations. For each 

land-use class, average values of parameters controlling the 

sediment loads used in the Chesapeake Bay watershed model 

were taken as initial estimates in the calibration. Tillage 

practices were incorporated for the simulation of corn, double crops, and vegetables.

Manual calibration, soils information, and other studies 

in the watershed were used to determine the best set of 

parameters for the simulation of nutrients. Nitrogen and 

phosphorus first-order reaction parameters were estimated 

for the surface, upper, lower, and active ground-water layers 

through simultaneous calibration of the land and in-stream 

nutrient processes.

For the simulation of the manure hectare land-use class, 

loading rates of BOD, organic nitrogen, and organic phosphorus were obtained from the Chesapeake Bay watershed 

model (U.S. Environmental Protection Agency, 1998). BOD 

was expressed in terms of nitrogen (labile and refractory) 

with an assumed yield of 1,615 kg/ha (kilograms per hectare). The contributions of organic nitrogen and phosphorus 

were also expressed in terms of labile and refractory nitrogen 

with the following assumed loads: organic nitrogen (refractory) = 76.2 kg/ha; organic nitrogen (labile) = 9.3 kg/ha; 

organic phosphorus (refractory) = 3.8 kg/ha, and organic 

phosphorus (labile) = 0.98 kg/ha.

For the forest land-use class, a more detailed simulation 

of the behavior of nitrogen in the soil profile was performed, 

in which ammonium and two forms of particulate organic 

nitrogen (labile and refractory) were allowed to adsorb onto 

sediment. These forms of nitrogen, once adsorbed, could 

potentially be removed from storage on the land surface during surface runoff.

Predicted total nitrogen and total phosphorus edge-ofstream yields for croplands were compared to the range of 

values from work conducted at the University of Maryland 

Wye Research and Education Center (Staver and Brinsfield, 

1998); the purpose of this comparison was to ensure that the 

model predictions were within the observed range of values.

Accumulation and depletion rates of constituents simulated in the impervious land (ammonium, nitrate, phosphate, 

and BOD) were determined through the calibration of the 

Munchy Branch Basin. This basin was selected because 

30 percent of it is impervious land, and the load contribution 

of the impervious area was crucial in obtaining a good calibration. These rates were adopted for the simulation of 

impervious areas in the remaining model segments.

The in-stream simulation includes the primary processes 

that determine the balance of inorganic nitrogen and phosphorus in natural waters. The processes are:

1. longitudinal advection of dissolved nitrate, nitrite, 

ammonia, and orthophosphate;

2. benthic release of ammonia and orthophosphate;

3. benthic uptake of nitrate, ammonia, and 

orthophosphate;

4. ammonia ionization (ammonia/ammonium 

equilibrium);

5. ammonia vaporization;

6. nitrification of ammonia and nitrite;

7. denitrification;

8. ammonification due to degradation of BOD 

materials;

9. adsorption/desorption of ammonia and 

orthophosphate to/from inorganic sediment in the 

water column; and

10. deposition/scour and longitudinal advection of 

adsorbed ammonia and orthophosphate.

Phytoplankton (free-floating photosynthetic algae) and 

benthic algae (the state variable for algae attached to the 

benthic surface) were included in the simulation after analysis of observed data for phosphate. Benthic algae uptake of 

phosphate occurs primarily during the winter, and phytoplankton uptake occurs primarily during the summer.

Analysis of Model Calibration and Results

Parameter estimation techniques and manual calibration 

were used to determine the best hydrologic parameters for 

the model, using observations of hourly and mean daily 

streamflow from the five single-segment calibration sites 

(segment numbers 010, 030, 130, 310, and 330) for the 

period of record (table 18). Parameter values for the calibration of water-quality components were obtained through 

manual calibration. Model parameters were extrapolated to 

the non-calibrated model segments on the basis of HGMR 

and soils characteristics and proximity to calibrated segments (fig. 6).

The accuracy of the model was evaluated in several 

ways. During calibration, goodness-of-fit statistics and 

visual examination were used to refine parameter estimates. 

Time series of simulated streamflow, simulated edge-ofstream streamflow components, observed streamflow, and 

simulated and observed water chemistry, at hourly and daily 

time steps, were developed during calibration. These were 

analyzed during the calibration process to determine how 

well the model represented the natural system dynamics. 

Edge-of-stream nutrient loads were checked following calibration to ensure consistency with expected values and 

results of other modeling efforts in the region.
Analysis of Model Calibration and Results 25
26 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed

Once calibrated, the output was summarized by integrating over months or years to produce monthly and annual 

streamflow and loads; loads could then be divided by segment area to determine yields for each of the 45 model segments. Model parameters for all land uses varied spatially 

and (in some cases) temporally; these variations were generally consistent with soil type, properties of the aquifer, 

topography, degree of ditching and other human influences, 

and observations of annual streamflow during the periods for 

which data were available.

Calibration of Hydrology

Goodness-of-fit statistics were calculated between the 

observed and simulated daily streamflow values to evaluate 

the model performance for the six calibrated basins (table 

20). Results for the relative bias indicate that the simulations were within 19 percent of the observed values for all 

basins. The relative standard error is large for Beaverdam 

Ditch, which may be related in part to uncertainty in the precipitation data (especially timing) and the fact that only one 

channel rather than a network of channels is simulated 

within a model segment.

Annual and Monthly Water Balance Simulated annual 

streamflow provided a critical check on model performance. 

The simulated annual streamflow from the six calibrated 

watersheds (table 20) was consistent, within 20 percent, with 

the observed values (see relative bias in table 20). Streamflow was lower throughout the watershed in 1999 because of 

the drought, with Swan Creek only discharging 46 mm of 

streamflow, while receiving more than 1,000 mm of precipitation. Higher streamflow was observed in the southern part 

of the watershed (segments 310 and 330) than in the northern 

part (segments 010, 030, and 130). This was expected 

because the sub-basins are located in the surficial confined 

HGMR (fig. 1a), where the storage capacity of the aquifer 

material is expected to be relatively low. This is reflected in 

the model parameter values for the lower zone nominal storage (LZSN), which are 150 mm for Beaverdam Creek and 

230 mm for Blackwater Creek. These storage values are 

low in comparison to those in the northern basins in the welldrained upland HGMR, which are 380 mm for Swan Creek 

and 520 mm for Bundicks Branch. Ditching is a common 

practice, especially in the southern basins, to increase drainage capacity and to maintain optimal soil conditions for 

crops. The effects of ditching from a hydrologic standpoint 

are shorter ground-water-flow paths and larger amounts of 

streamflow.

Monthly simulated and observed streamflow values 

(fig. 7) show good agreement, with most simulated values 

within 30 percent of the observed values. Seasonality in 

streamflow was captured by the model, in part due to the 

seasonality in available moisture, but also through adjustment of storage parameters that varied monthly. Streamflow 

in September 1999 reflected the contribution from Hurricane 

Floyd in mid-September. The model was generally able to 

capture this large event and the simulated and observed 

streamflow for September are in close agreement for all segments with one exception. Streamflow during September 

1999 at Swan Creek was over-simulated, possibly due to the 

difficulty in handling wetlands, which dominate the riparian 

area in the lower part of the basin.

 

Table 20. Goodness-of-fit statistics for comparison of simulated and observed mean 

 daily streamflow at the six calibration stations for 1999

[mm, millimeters]

Station name

Annual 

precipitation 

(mm)

Predicted 

annual 

streamflow 

(mm)

Observed 

annual 

streamflow 

(mm)

Number of

values,

N

Relative 

bias 1

Relative 

standard 

error 2

Munchy Branch near Rehoboth Beach, DE 1,072 176 170 365 0.03 0.45

Bundicks Branch at Robinsonville, DE 1,072 111 112 365 -0.01 0.55

Swan Creek near Millsboro, DE 1,090 52 46 365 0.13 0.80

Blackwater Creek near Clarkesville, DE 1,090 301 253 365 0.19 0.63

Beaverdam Ditch near Millville, DE 1,090 473 432 365 0.09 1.35

Millsboro Pond Outlet at Millsboro, DE 1,092 387 376 365 0.03 0.95

1 Relative bias = sum[(simulated – observed)/N]/mean observed

2 Relative standard error = sqrt[sum(simulated – observed)2/(N – 1)]/sqrt[sum(mean observed – observed)2/(N – 1)]
Analysis of Model Calibration and Results 27
28 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed

Mean Daily Streamflow Time Series Time series of daily 

simulated and observed flows (fig. 8) and the edge-of-stream 

streamflow components (base flow, or active ground-water 

discharge, interflow, and surface runoff; fig. 9) were used to 

assess the model's ability to capture dynamic features of the 

hydrologic response in each of the calibrated basins. 

Streamflow response in these basins may be characterized by 

the rate of hydrograph rise in response to precipitation, the 

magnitude of peak flows, and the rate of recession. In addition, seasonality in base flow and total streamflow reflect the 

processes occurring in the Inland Bays watershed, and the 

flow paths responsible for chemical loading.

Recession rate is a critical aspect of watershed hydrologic response. Parameters in the model were adjusted so 

that the base-flow and interflow recession rates closely 

matched observations. Base-flow recession is fastest in 

Blackwater Creek (segment 310) and Beaverdam Ditch (segment 330) within the surficial confined HGMR (fig. 1a) 

where soils are generally less permeable than in other parts 

of the watershed (fig. 2). A strong seasonality to base flow 

is also observed in these basins (fig. 8), indicating the importance of seasonal variations in moisture supply and evapotranspiration.

Interflow is more important in the southern basins than in 

the northern basins (Blackwater Creek and Beaverdam Ditch 

basins, fig. 9). In this case, it seems that the processes 

represented by the model show the effects of ditching, which 

shortens the ground-water flow paths, thereby increasing the 

amount of interflow during the fall, winter, and spring. 

The effects of soil type, aquifer properties, and land use 

on runoff response are shown by the total runoff of each 

component for the calibrated basins (table 21). The predominantly urban watershed drained by Munchy Branch 

(segment 010) has a major surface-runoff component, as 

would be expected for an area that is largely impervious. In 

1999, 31 percent of the simulated streamflow for Munchy 

Branch was from overland flow. The remainder was predominantly base flow. The intermediate interflow reservoir 

is not a significant contributor to streamflow, accounting for 

only 7 percent of the total. Bundicks Branch Basin (segment 030) has less urban area and is almost one-half agricultural (table 2), and therefore has lower surface runoff. Soil 

type and aquifer properties in the Bundicks Branch Basin are 

similar to those of the Munchy Branch Basin, with relatively 

high permeability and infiltration rate; base flow is the largest component of runoff in both watersheds. Further west 

and southwest, Swan Creek (segment 130) has the highest 

amount of base flow, as would be expected during a drought 

year in a forested watershed with relatively permeable aquifer materials. As land use changes from urban through agriculture to forest, base flow increases and surface runoff 

decreases.

 

Table 21. Simulated annual edge-of-stream runoff components for the five single-segment

 calibrated basins during 1999

[mm, millimeters]

Edge-of-stream components

Base flow Interflow Surface runoff

Segment Name mm

fraction

of total mm

fraction

of total mm

fraction

of total

010 Munchy Branch near Rehoboth Beach, DE 108 0.62 12 0.07 53 0.31

030 Bundicks Branch at Robinsonville, DE 85 0.77 4.8 0.04 21 0.19

130 Swan Creek near Millsboro, DE 44 0.84 3.3 0.06 4.9 0.09

310 Blackwater Creek near Clarkesville, DE 172 0.57 108 0.36 21 0.07

330 Beaverdam Ditch near Millville, DE 221 0.47 114 0.24 135 0.29
Analysis of Model Calibration and Results 29
30 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed
Analysis of Model Calibration and Results 31

 

Calibration of Total Suspended Solids

The accuracy of the model was evaluated through examination of time series of observed and simulated TSS concentrations. Because of the strong positive correlation between 

streamflow and sediment concentration, it was often necessary to make small adjustments to the hydrology parameters 

to achieve a more accurate simulation of TSS.

Annual Edge-Of-Stream Yields TSS simulated edge-ofstream yields (table 22) during water year 1999C may not be 

representative of the loads during an average hydrologic 

year. The drought of 1999 and Hurricane Floyd in September provided two extreme hydroclimatological conditions 

that must be taken into account when extrapolating the simulated edge-of-stream yields to other years.

In general, the amount of surface runoff, the degree of 

urbanization, and the presence or absence of riparian buffers 

or wetlands influences the amount of detached sediment 

delivered to the streams. Simulated TSS yields are strongly 

linked to annual streamflow, and are generally lower in the 

northern basins than in the southern basins (fig. 10).

The difference in yields in the northern and southern 

basins can be explained in terms of the HGMR classification 

and the agricultural practices in both areas. The amount of 

organic material and permeability are lower in the southern 

basins than in the northern basins; intense ditching is commonly practiced in the southern basins to increase drainage 

and maintain optimum soil conditions for the crops. In the 

northern basins, higher organic matter content and higher 

permeability reduce the potential for TSS transport. In addition, ditching and ditch maintenance in the southern basins 

provide a possible additional source of sediment.

Relative to other northern basins, the TSS yield for 

Munchy Branch is high (table 22), which may result from 

the predominance of urban land within the basin, and the 

location of the basin outlet within an urban area. In contrast, 

Swan Creek is predominantly a forested basin with significant vegetated buffers and wetlands along the stream that 

attenuate the loads from all land uses. TSS is transported 

only in overland flow and therefore may have a zero yield 

for land-use classes with no simulated overland flow, as is 

the case for forest and pervious urban land-use classes in the 

Munchy Branch Basin and all land-use classes except impervious urban in the Blackwater Creek Basin.

Hourly Concentration Time Series Time series of hourly 

simulated and observed TSS concentrations (fig. 11) were 

used to assess the model's ability to capture dynamic features 

of the sediment runoff response in each of the calibrated segments. Because sediment runoff increases with streamflow 

and the fraction of streamflow that is surface or overland 

flow, TSS dynamics closely resemble the dynamics of 

streamflow and surface runoff (see figs. 9 and 11). TSS also 

includes organic material and may therefore display a seasonality related to summer growth of algae.

Calibration of Nutrients

Nutrient applications varied in type (organic or mineral 

fertilizer), amount, and timing of application. The type is 

determined by the location of manure production throughout 

the watershed. For the Munchy Branch and Swan Creek 

Basins, only mineral fertilizer was applied to fulfill 

thecrops’ nutrient requirement; the amount applied was 

assumed to be 110 percent of the amount necessary to meet 

the crop goal yield. The timing was assumed to be optimum, just prior to the growing season. The effect of these 

assumed conditions can be seen mainly in the concentrations 

of total nitrogen, which are generally lower in Munchy 

Branch and Swan Creek than in any other monitored stream.

Table 22. Simulated edge-of-stream total suspended solids yields by land-use class for the 

 five single-segment calibrated basins during water year 1999

[All values are in kilograms per hectare per year]

Segment Forest Corn Double

crops

Full-season

soybeans

Hay Vegetables Pasture Pervious

urban

Impervious

urban

Weighted

average

010 0.0 1.7×10−4 2.2×10−4 2.2×10−4 3.3×10−4 3.1×10−4 3.6×10−4 0.0 43 26

030 3.9×10−4 1.5×10−4 1.0×10−4 1.6×10−4 2.0×10−4 2.0×10−4 2.6×10−4 5.2×10−2 140 3.2

130 3.7×10−3 2.0×10−2 1.7×10−2 2.5×10−2 2.9×10−2 2.8×10−2 3.8×10−2 3.8×10−2 92 0.8

310 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1,300 36

330 140 130 83 130 130 130 130 120 410 130

C. Total suspended solids and nutrient yields are reported on a water year basis rather than a calendar year basis, because soil conditions were reset in 

the model at the beginning of each water year. Water year 1999 is October 1, 1998 through September 30, 1999.
32 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed
Analysis of Model Calibration and Results 33
34 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed

 

Annual Edge-Of-Stream Yields The simulation of hydrologic and chemical processes in the soil and aquifer leads to 

the simulation of edge-of-stream loads and yields (tables 23 

and 24). Due to the dry conditions during water year 1999, 

low edge-of-stream yields were expected. For total nitrogen 

(table 23), the simulated forest land had the lowest yields for 

all calibrated segments in comparison to yields from other 

land-use classes, and a trend of increasing total nitrogen 

yield is observed from north to south (fig. 12). The main 

nitrogen species in the edge-of-stream yields from forest 

land is organic nitrogen, whereas phosphorus is primarily in 

the inorganic form (orthophosphate).

In water year 1999, total nitrogen yields from cropland 

were higher for the southern basins (segments 310 and 330) 

than for the northern basins (table 23). In the southern 

basins, the application of organic fertilizer (animal waste) 

exceeded the recommended rates, and annual streamflow 

was higher. In the simulation of cropland and forest land, 

the majority of inorganic nutrient (nitrate, orthophosphate) 

loads are transported through base flow, followed by interflow. As was expected for all of the simulated constituents, 

the impervious urban yields were higher than yields from the 

pervious urban category. Pervious urban yields for total 

nitrogen ranged from 0.28 kg/ha/yr to 4.5 kg/ha/yr in water 

year 1999, compared to the impervious urban yields, which 

ranged from 3.7 kg/ha/yr to 6.2 kg/ha/yr. Pervious urban 

areas provided the major load during base flow, and the 

impervious land provided the load during storm events.

In Munchy Branch, the calibration emphasizes the urban 

land response; 66 percent of the basin area is urban. The 

lowest total nitrogen yields occurred in Munchy Branch 

(segment 010) and Swan Creek (segment 130), where the 

nutrient application was limited to mineral fertilizer at the 

optimum rate and timing, and the streamflow was low during 

1999 (Munchy Branch had 170 mm and Swan Creek had 

46 mm). Significant attenuation of loads between the 

Table 23. Simulated edge-of-stream total nitrogen yields by land-use class for the 

 five single-segment calibrated basins during water year 1999

[All values are in units of kilograms per hectare per year]

Segment Forest Corn Double

crops

Full-season

soybeans

Hay Vegetables Pasture Pervious

urban

Impervious

urban

Weighted

average

010 0.17 3.2 3.0 3.2 2.9 3.2 1.0 1.5 4.4 2.0

030 0.41 8.8 9.4 4.9 44 8.3 2.0 1.8 5.4 4.0

130 0.27 1.8 1.4 0.96 0.68 1.3 0.32 0.28 3.7 0.53

310 0.90 27 23 20 130 22 3.9 4.1 5.3 16

330 2.6 28 19 22 71 20 3.8 4.5 6.2 18

Table 24. Simulated edge-of-stream total phosphorus yields by land-use class for the 

 five single-segment calibrated basins during water year 1999

[All values are in units of kilograms per hectare per year]

Segment Forest Corn Double

crops

Full-season

soybeans

Hay Vegetables Pasture Pervious

urban

Impervious

Urban

Weighted

average

010 2.3×10−2 2.9×10−2 2.2×10−2 2.6×10−2 1.2×10−2 6.9×10−2 1.2×10−2 1.7×10−2 6.5×10−1 5.9×10−2

030 6.3×10−3 2.1×10−2 2.0×10−2 9.3×10−3 2.1×10−2 2.0×10−2 2.2×10−2 6.0×10−2 8.5×10−1 3.4×10−2

130 6.6×10−4 5.0×10−3 4.2×10−3 9.3×10−3 4.3×10−3 1.0×10−2 7.8×10−3 1.8×10−2 5.0×10−1 7.7×10−3

310 1.6×10−2 6.7×10−1 2.4×10−2 1.6×10−1 9.0×10−1 8.9×10−1 1.5×10−1 1.5×10−1 2.4×10−1 2.6×10−1

330 3.7×10−2 6.2×10−1 1.8×10−1 2.1 1.9 2.1 3.1×10−1 2.1×10−1 9.3×10−1 9.4×10−1
Analysis of Model Calibration and Results 35

ERRATA SHEET REVISED 3-10-2006 TO REPLACE PAGE 35
36 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed

edge-of-stream and the end-of-reach occurs in Swan Creek, 

due to processing within forested buffers and riparian wetlands.

Phosphorus yields (fig. 13) were linked to sediment 

yields (see figs. 11 and 14), because phosphorus attaches 

strongly to soil particles, and therefore appears in low concentrations in water but in high concentrations on the soil 

particles. For the northern basins, the amount of nutrients 

immobilized through sorption was higher near the surface, 

whereas for the southern basins, immobilization increased 

with depth. 

Three of the basins were predominantly agricultural: 

Bundicks Branch with 48 percent of the total area, Blackwater Creek with 66 percent of the total area, and Beaverdam 

Ditch with 70 percent of the total area. However, several 

factors caused the edge-of-stream yields for these three 

basins to vary by as much as an order of magnitude. 

Bundicks Branch is in the northern part of the watershed 

within a well-drained terrain, the nutrient application was at 

the recommended rates (although there was application of 

organic fertilizer), and there is relatively little ditching; thus 

it was expected that the edge-of-stream yields would be 

lower than in Blackwater Creek or Beaverdam Ditch. In 

contrast, Blackwater Creek and Beaverdam Ditch are in the 

southern part of the watershed within a poorly drained 

region, where ditching is widespread to promote soil drainage, shallow stream incision is observed, and there is a need 

to over-apply organic fertilizer to dispose of the manure production; these factors contributed to the highest expected 

values of the edge-of-stream yields in the watershed. In 

Beaverdam Ditch Basin, for example, the application rate for 

the croplands was twice the recommended rate for nitrogen 

and phosphorus.

Hourly Concentration Time Series The primary goal in 

developing a watershed model for the Delaware Inland Bays 

was to allow prediction of loads. In general, watershed models perform better when model output and observations are 

integrated or averaged over longer times. Therefore, it is 

more likely that dynamic watershed models will perform 

best when comparing simulated and observed monthly or 

annual loads or flows. Due to the nature of the temporal 

variance in nutrient concentrations in streams, however, it is 

conceptually possible for a watershed model to accurately 

predict annual flow or load, yet incorrectly capture the 

dynamics of the processes responsible. Therefore, hourly 

simulated and instantaneous observed values were compared 

during the calibration process to improve the ability of the 

model to predict loading and natural process dynamics.

Time series of simulated hourly total nitrogen and phosphorus concentrations and observed instantaneous values are 

shown in figures 14 and 15. Seasonality was reflected in the 

observed and simulated total nitrogen concentrations, with 

the lowest values during the summer and the highest during 

the winter. During storm events, total nitrogen concentrations tend to be diluted and total phosphorus concentrations 

tend to rise sharply. Nitrogen is transported mainly in the 

aqueous phase and largely through ground water, although 

phosphorus is strongly associated with sediment that washes 

off during precipitation events. There are exceptions to these 

generalizations, but figures 14 and 15 demonstrate the ability 

of the model to simulate the dynamic processes responsible 

for in-stream nutrient concentrations on an hourly basis.
Analysis of Model Calibration and Results 37
38 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed
Analysis of Model Calibration and Results 39
40 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed

Summary and Conclusions

A cooperative study involving the Delaware Department 

of Natural Resources and Environmental Control, the

Delaware Geological Survey, and the U.S. Geological 

Survey was initiated in 2000 to develop a hydrologic and 

water-quality model of the Delaware Inland Bays watershed 

that can be used as a water-resources planning and management tool. The model code used was Hydrological 

Simulation Program-FORTRAN (HSPF), which is well documented. Hydrologic, agricultural, meteorological, and 

water-quality data were compiled from 1998 through 2000, 

and used for the development and calibration of the model. 

The 719-square-kilometer watershed was divided into 45 

model segments and the model was calibrated using streamflow and water-quality data from six U.S. Geological Survey 

stream-gaging stations within the watershed. Calibration for 

some parameters was accomplished using PEST, a modelindependent parameter estimator. Model parameters were 

adjusted systematically so that the discrepancies between the 

simulated values and the corresponding observations were 

minimized.

Model accuracy was evaluated in several ways. During 

calibration, goodness-of-fit statistics and visual examination 

were used to refine parameter estimates. Time series of simulated streamflow, simulated edge-of-stream runoff components, observed streamflow, and simulated and observed 

water chemistry, at hourly and daily time steps, were developed during calibration. These were examined during the 

calibration process to determine how well the model represented the natural system dynamics. Edge-of-stream nutrient loads were checked following calibration to ensure 

consistency with expected values and results of other modeling efforts in the region.

Model parameters for all land uses varied spatially and 

(in some cases) temporally; these variations were generally 

consistent with soil type, aquifer properties, topography, 

degree of ditching and other human influences, and observations of annual streamflow during the period of available 

data. The simulated annual streamflow from the six calibrated watersheds was consistent with the observed values, 

and was reduced throughout the watershed in 1999 because 

of the drought. Soil and aquifer permeability, ditching, and 

land-use practices affect the amount of streamflow and the 

hydrologic mechanism or flow path (surface flow, interflow, 

or base flow). Greater streamflow was observed in the 

southern part of the watershed than in the northern part. The 

flatness of the terrain and the low annual surface runoff are 

important factors in the amount of detached sediment from 

the land that was delivered to streams. The highest total suspended solids yields occurred in the southern part of the 

watershed. Blackwater Creek and Beaverdam Ditch Basins 

had high sediment yields associated with high streamflow 

and a high fraction of surface runoff.

In the simulation of agricultural and forest land throughout the Inland Bays watershed, the majority of inorganic 

nutrient (nitrate, orthophosphate) loads are transported 

through base flow, followed by interflow. Nutrient yields 

from Beaverdam Ditch and Blackwater Creek Basins were 

the highest of all calibrated basins, because both basins 

experienced high streamflow, and the amount of organic fertilizer (animal waste) available in both basins led to overapplication of organic fertilizer to the crops.

Time series of simulated hourly total nitrogen and phosphorus concentrations and observed instantaneous values 

indicate seasonality in the observed and simulated concentrations for total nitrogen, with the lowest values during the 

summer and the highest during the winter months. Phosphorus is somewhat less seasonal; in general, base-flow total 

phosphorus concentrations were low, typically less than 

0.05 milligrams per liter. During storm events, total nitrogen concentrations tend to be diluted and total phosphorus 

concentrations tend to rise sharply. Nitrogen is transported 

mainly in the aqueous phase and primarily through ground 

water, whereas phosphorus is strongly associated with sediment, which washes off during precipitation events.

References Cited

Andres, A.S., 1987, Geohydrology of the northern coastal 

area, Delaware-sheet 2, Geohydrology of the Columbia 

aquifer: Delaware Geological Survey Hydrologic Map 

Series No. 5, scale 1:24,000.

______1991, Results of the coastal Sussex County, 

Delaware ground-water quality survey: Delaware 

Geological Survey Report of Investigations No. 49, 28 p.

Andres, A.S., Savidge, K.B., Scudlark, J.R., and Ullman, 

W.J., 2002, Delaware Inland Bays tributary Total 

Maximum Daily Load water-quality database: Delaware 

Geological Survey Digital Product No.02–02, version 

6.62.

Bachman, L.J., and Wilson, J.M., 1984, The Columbia 

aquifer of the Eastern Shore of Maryland: Maryland 

Geological Survey Report of Investigations No. 40, 

144 p.

Bicknell, B.R., Imhoff, J.C., Kittle, J.L., Jr., and 

Donigian, A.S., Jr., 1996, Hydrological Simulation 

Program-FORTRAN user's manual for Release 11:

U.S. Environmental Protection Agency, 755 p.

Delaware Department of Natural Resources and 

Environmental Control, 1998, Final determination for 

the State of Delaware 1998 Clean Water Act Section 

303(d) list of waters needing TMDLs, accessed 

May 6, 2003 at http://www.dnrec.state.de.us/dnrec2000/

Library/Water/303(d)list.pdf

Delaware Geological Survey, 2003, Correlation of 

hydrologic units to geologic units recognized in 

Delaware by the Delaware Geological Survey in the 

Delaware Coastal Plain, accessed April 17, 2003 at http:/

/www.udel.edu/dgs/Hydrology/hydrostrat.html
References Cited 41

Delaware Office of State Planning Coordination, 2002, 

1997 Landuse/Landcover Data–GIS Data, accessed

April 21, 2003 at http://www.state.de.us/planning/info/

lulcdata/lulc.htm

Denver, J.M., 1989, Effects of agricultural practices and 

septic-system effluent on the quality of water in the 

unconfined aquifer in parts of eastern Sussex County, 

Delaware: University of Delaware Report of 

Investigations No. 45, 66 p.

Dillow, J.J.A., and Greene, E.A., 1999, Ground-water 

discharge and nitrate loadings to the coastal bays of 

Maryland: U.S. Geological Survey Water-Resources 

Investigations Report 99–4167, 8 p.

Doherty, J., 2000, PEST: Model-independent parameter 

estimation: Watermark Numerical Computing, 247 p.

Donigian, A.S., Jr., Bicknell, B.R., and Imhoff, J.C., 1995, 

Hydrological Simulation Program - FORTRAN (HSPF), 

in Singh, V.P., ed., Computer models of watershed 

hydrology: Water Resources Publications, p. 395–442.

Gutiérrez-Magness, A.L., and McCuen, R.H., 2002, Is 

automatic fitting automatic in model optimization?: 

Eos, Transactions, American Geophysical Union,

Spring Meeting Supplement, Abstract H52B–02,

v. 83, no. 19.

Hamilton, P.A., Denver, J.M., Phillips, P.J., and 

Shedlock, R.J., 1993, Water-quality assessment of the 

Delmarva Peninsula, Delaware, Maryland, and Virginia–

Effects of agricultural activities on, and distribution of, 

nitrate and other inorganic consituents in the surficial 

aquifer: U.S. Geological Survey Open-File Report 

93–40, 87 p.

Hamon, W.R., 1961, Estimating potential 

evapotranspiration: Journal of the Hydraulics Division, 

American Society of Civil Engineers, v. 87, p. 107–120.

Johnston, R.H., 1976, Relation of ground water to surface 

water in four small basins of the Delaware Coastal Plain: 

Delaware Geological Survey Report of Investigations 

No. 24, 56 p.

Kuczera, G., 1983, Improved parameter inference in 

catchment models. 1. Evaluating parameter uncertainty: 

Water Resources Research, v. 19, no. 5, p. 1,151–1,172.

Lander, C.H., Moffitt, D., and Klaus, A., 1998, Nutrients 

available from livestock manure relative to crop growth 

requirements: Appendix I—Nutrient uptake and 

removal: U.S. Department of Agriculture:

Natural Resources Conservation Service, accessed

April 21, 2003 at http://www.nrcs.usda.gov/technical/

land/pubs/nlapp1a.html

Maizel, M.S., Muehlbach, G., Baynham, P., Zoerkler, J., 

Monds, D., Iivari, T., Welle, P., Robbin, J., and 

Wiles, J., 1997, The potential for nutrient loadings from 

septic systems to ground and surface water resources and 

the Chesapeake Bay: U.S. Environmental Protection 

Agency EPA #903–R–97–006, 280 p.

Miller, J.C., 1972, Nitrate contamination of the water-table 

aquifer in Delaware: Delaware Geological Survey 

Report of Investigations No. 20, 36 p.

National Oceanic and Atmospheric Administration, 

2001, National Climatic Data Center, accessed

May 8, 2003 at http://www.ncdc.noaa.gov/oa/ncdc.html

Phillips, P.J., and Bachman, L.J., 1996, Hydrologic 

landscapes on the Delmarva Peninsula - Part 1: Drainage 

basin type and base-flow chemistry: Journal of the 

American Water Resources Association, v. 32, no. 4,

p. 767–778.

Robertson, F.N., 1977, The quality and potential problems 

of the ground-water in coastal Sussex County, Delaware: 

University of Delaware Water Resources Center, 58 p.

Schwarz, G.E., and Alexander, R.B., 1995, State soil 

geographic (STATSGO) data base for the conterminous 

United States version 1.1 (scale 1:250,000): U.S. 

Geological Survey Open-File Report 95–449.

Scudlark, J.R., and Church, T.M., 2001, A comprehensive 

reexamination of the input of atmospheric nitrogen to the 

Rehoboth and Indian River Estuaries: Delaware Center 

for the Inland Bays, 39 p.

Shedlock, R.J., Denver, J.M., Hayes, M.A., Hamilton, 

P.A., Koterba, M.T., Bachman, L.J., Phillips, P.J., and 

Banks, W.S.L., 1999, Water-quality assessment of the 

Delmarva Peninsula, Delaware, Maryland, and Virginia: 

Results of investigations, 1987–91: U.S. Geological 

Survey Water-Supply Paper 2355–A, 41 p.

Sims, J.T., and Wolf, D.C., 1993, Poultry waste 

management: Agricultural and environmental issues: 

Advances in Agronomy, v. 52, p. 1–81.

Sprague, L.A., Langland, M.J., Yochum, S.E., Edwards, 

R.E., Blomquist, J.D., Phillips, S.W., Shenk, G.W., and 

Preston, S.D., 2000, Factors affecting nutrient trends in 

major rivers of the Chesapeake Bay Watershed: U.S. 

Geological Survey Water-Resources Investigations 

Report 00–4218, 98 p.

Staver, K.W., and Brinsfield, R.B., 1998, Using cereal 

grains to minimize nitrogen leaching losses: University 

of Maryland, College of Agriculture and Natural 

Rersources, Wye Research and Education Center Final 

Report - Grant 98107, [variously paged].

Talley, J.H., 1988, Geohydrology of the southern coastal 

area, Delaware-sheet 2, Geohydrology of the Columbia 

aquifer: Delaware Geological Survey Hydrologic Map 

Series No. 7, scale 1:24,000.

U.S. Department of Agriculture: National Agricultural 

Statistics Service, 1997a, Census of agriculture, 

accessed April 18, 2003 at http://www.nass.usda.gov/

census/

______ 1997b, Usual planting and harvesting dates for 

U.S. field crops, accessed April 22, 2003 at http://

www.usda.gov/nass/pubs/uph97.htm

______ 2003, Delaware Agricultural Statistics Service, 

accessed April 21, 2003 at http://www.nass.usda.gov/de/

U.S. Department of Agriculture: Natural Resources 

Conservation Service, 2003, CNMP Workbook: manure 

application rates, accessed July 18, 2003 at http://

www.wy.nrcs.usda.gov/technical/wycnmp/sec13.html
42 Hydrologic and Water-Quality Model of the Delaware Inland Bays Watershed

U.S. Environmental Protection Agency, 1997, Chesapeake 

Bay Watershed model application and calculation of 

nutrient and sediment loadings, Appendix D: Phase IV 

Chesapeake Bay Watershed model precipitation and 

meteorological data development and atmospheric 

nutrient deposition: U.S. Environmental Protection 

Agency, 58 p.

______ 1998, Chesapeake Bay Watershed model application 

and calculation of nutrient and sediment loadings, 

Appendix H: Tracking best management practice 

nutrient reductions in the Chesapeake Bay Program: 

U.S. Environmental Protection Agency, 91 p.

______ 2003, Clean water act, accessed May 6, 2003 at 

http://www.epa.gov/region5/water/cwa.htm

Ullman, W.J., Andres, A.S., Scudlark, J.R., and Savidge, 

K.B., 2002, Storm-water and base-flow sampling and 

analysis in the Delaware Inland Bays: Preliminary report 

of findings, 1998-2000: Delaware Geological Survey 

Open-File Report No. 44, 40 p.

University of Delaware Spatial Analysis Lab, 2003, 

30-meter resolution Digital Elevation Models for 

Delaware and Chester County, PA, accessed 

May 7, 2003 at http://www.udel.edu/FREC/spatlab/dems/

dem_intro.html

Wheeler, J.C., 1999, Freshwater use in Delaware, 1995:

U.S. Geological Survey Fact Sheet FS-126-99, 2 p.